Towards data-driven quantification of skin ageing using reflectance confocal microscopy.

INTRODUCTION: Evaluation of skin ageing is a non-standardized, subjective process, with typical measures relying coarse, qualitatively defined features. Reflectance confocal microscopy depth stacks contain indicators of both chrono-ageing and photo-ageing. We hypothesize that an ageing scale could be constructed using machine learning and image analysis, creating a data-driven quantification of skin ageing without human assessment. METHODS: En-face sections of reflectance confocal microscopy depth stacks from the dorsal and volar forearm of 74 participants (36/18/20 training/testing/validation) were represented using a histogram of visual features learned using unsupervised clustering of small image patches. A logistic regression classifier was trained on these histograms to differentiate between stacks from 20- to 30-year-old and 50- to 70-year-old volunteers. The probabilistic output of the logistic regression was used as the fine-grained ageing score for that stack in the testing set ranging from 0 to 1. Evaluation was performed in two ways: on the test set, the AUC was collected for the binary classification problem as well as by statistical comparison of the scores for age and body site groups. Final validation was performed by assessing the accuracy of the ageing score measurement on 20 depth stacks not used for training or evaluating the classifier. RESULTS: The classifier effectively differentiated stacks from age groups with a test set AUC of 0.908. Mean scores were significantly different when comparing age groups (mean 0.70 vs. 0.44; t = -6.62, p = 0.0000) and also when comparing stacks from dorsal and volar body sites (mean 0.64 vs. 0.53; t = 3.12, p = 0.0062). On the final validation set, 17 out of 20 depth stacks were correctly labelled. DISCUSSION: Despite being limited to only coarse training information in the form of example stacks from two age groups, the trained classifier was still able to effectively discriminate between younger skin and older skin. Curiously, despite being only trained with chronological age, there was still evidence for measurable differences in age scores due to sun exposure-with marked differences in scores on sun-exposed dorsal sites of some volunteers compared with less sun-exposed volar sites. These results suggest that fine-grained data-driven quantification of skin ageing is achievable.

INTRODUCTION: L'évaluation du vieillissement de la peau est un processus subjectif et non standardisé, dont les mesures typiques reposent sur des caractéristiques grossières et définies qualitativement. Les strates de profondeur observées grâce à la microscopie confocale par réflectance contiennent des indicateurs de chrono-vieillissement et de photo-vieillissement. Nous émettons l'hypothèse selon laquelle il serait possible d'établir une échelle de vieillissement à l'aide de l'apprentissage automatique et de l'analyse d'images, permettant la mise en place d'une quantification du vieillissement cutané fondée sur les données et sans évaluation humaine. MÉTHODES: À l'aide d'un histogramme des caractéristiques visuelles apprises à partir de petits ensembles d'images regroupées sans supervision, on a représenté des coupes faciales de strates de profondeur observées grâce à la microscopie confocale par réflectance et issues des faces dorsale et palmaire de l'avant-bras de 74 participants (36/18/20 entraînement/analyse/validation). Après un processus d'entraînement portant sur ces histogrammes, un classificateur de régression logistique a appris à différencier les strates prélevées sur des volontaires âgés de 20 à 30 ans et celles prélevées sur des volontaires âgés de 50 à 70 ans. Le résultat probabiliste de la régression logistique a été utilisé comme score du vieillissement de haute précision, allant de 0 à 1, pour cette strate dans l'ensemble d'analyse. L'évaluation a été effectuée de deux manières : dans l'ensemble d'analyse, l'aire sous la courbe (ASC) a été identifiée pour le problème de classification binaire ainsi que par comparaison statistique des scores selon les tranches d'âge et les catégories de site corporel. La validation finale est passée par une évaluation de l'exactitude de la mesure du score de vieillissement sur 20 strates de profondeur non utilisées dans le cadre du processus d'entraînement ou d'évaluation du classificateur. RÉSULTATS: Le classificateur différenciait efficacement les strates des tranches d'âge, avec une ASC dans l'ensemble d'analyse de 0,908. Les scores moyens affichaient des différences significatives lors de la comparaison entre les tranches d'âge (moyenne de 0,70 contre 0,44 ; t = 6,62 ; p = 0,0000) et lors de la comparaison entre les strates issues des faces dorsale et palmaire des sites corporels (moyenne de 0,64 contre 0,53 ; t = 3,12 ; p = 0,0062). Dans l'ensemble de validation finale, 17 strates sur 20 ont été correctement classées.

Investigation of the inherent left-right flow balancing of rotary total artificial hearts by means of a resistance box.

With the incidence of end-stage heart failure steadily increasing, the need for a practical total artificial heart (TAH) has never been greater. Continuous flow TAHs (CFTAH) are being developed using rotary blood pumps (RBPs), leveraging their small size, mechanical simplicity, and excellent durability. To completely replace the heart with currently available RBPs, two are required; one for providing pulmonary flow and one for providing systemic flow. To prevent hazardous states, it is essential to maintain balance between the pulmonary and systemic circulation at a wide variety of physiologic states. In this study, we investigated factors determining a CFTAH's inherent ability to balance systemic and pulmonary flow passively, without active management of pump rotational speed. Four different RBPs (ReliantHeart HA5, Thoratec HMII, HeartWare HVAD, and Ventracor VentrAssist) were used in various combinations to construct CFTAHs. Each CFTAH's ability to autonomously maintain pressures and flows within defined ranges was evaluated in a hybrid mock loop as systemic and pulmonary vascular resistance (PVR) were changed. The resistance box, a method to quantify the range of vascular resistances that can be safely supported by a CFTAH, was used to compare different CFTAH configurations in an efficient and predictive way. To reduce the need for future in vitro tests and to aid in their analysis, a novel analytical evaluation to predict the resistance box of various CFTAH configurations was also performed. None of the investigated CFTAH configurations fully satisfied the predefined benchmarks for inherent flow balancing, with the VentrAssist (left) and HeartAssist 5 (right) offering the best combination. The extent to which each CFTAH was able to autonomously maintain balance was determined by the pressure sensitivity of each RPB: the sensitivity of outflow to changes in the pressure head. The analytical model showed that by matching left and right pressure sensitivity the inherent balancing performance can be improved. These findings may ultimately lead to a reduced need for manual speed changes or active control systems.

A Starling-like total work controller for rotary blood pumps: An in vitro evaluation.

Due to improved durability and survival rates, rotary blood pumps (RBPs) are the preferred left ventricular assist device when compared to volume displacement pumps. However, when operated at constant speed, RBPs lack a volume balancing mechanism which may result in left ventricular suction and suboptimal ventricular unloading. Starling-like controllers have previously been developed to balance circulatory volumes; however, they do not consider ventricular workload as a feedback and may have limited sensitivity to adjust RBP workload when ventricular function deteriorates or improves. To address this, we aimed to develop a Starling-like total work controller (SL-TWC) that matched the energy output of a healthy heart by adjusting RBP hydraulic work based on measured left ventricular stroke work and ventricular preload. In a mock circulatory loop, the SL-TWC was evaluated using a HeartWare HVAD in a range of simulated patient conditions. These conditions included changes in systemic hypertension and hypotension, pulmonary hypertension, blood circulatory volume, exercise, and improvement and deterioration of ventricular function by increasing and decreasing ventricular contractility. The SL-TWC was compared to constant speed control where RBP speed was set to restore cardiac output to 5.0 L/min at rest. Left ventricular suction occurred with constant speed control during pulmonary hypertension but was prevented with the SL-TWC. During simulated exercise, the SL-TWC demonstrated reduced LVSW (0.51 J) and greater RBP flow (9.2 L/min) compared to constant speed control (LVSW: 0.74 J and RBP flow: 6.4 L/min). In instances of increased ventricular contractility, the SL-TWC reduced RBP hydraulic work while maintaining cardiac output similar to the rest condition. In comparison, constant speed overworked and increased cardiac output. The SL-TWC balanced circulatory volumes by mimicking the Starling mechanism, while also considering changes in ventricular workload. Compared to constant speed control, the SL-TWC may reduce complications associated with volume imbalances, adapt to changes in ventricular function and improve patient quality of life.

Closed-form equation to estimate the dielectric properties of biological tissues as a function of age.

Developing microwave systems for biomedical applications requires accurate dielectric properties of biological tissues for reliable modeling before prototyping and subject testing. Dielectric properties of tissues decrease with age due to the change in their water content, but there are no detailed age-dependent data, especially for young tissue-like newborns, in the literature. In this article, an age-dependent formula to predict the dielectric properties of biological tissues was derived. In the proposed method, the variation of water concentration in each type of tissue as a function of age was used to calculate its relative permittivity and conductivity. The derived formula shows that the concentration of water in each tissue type can be modeled as a negative exponential function of age. The dielectric properties of each tissue type can then be calculated as a function of the dielectric properties of water and dielectric properties of the organ forming the tissue and its water concentration. The derived formula was used to generate the dielectric properties of several types of human tissues at different ages using the dielectric properties of a human adult. Moreover, the formula was validated on pig tissues of different ages. A close agreement was achieved between the calculated and measured data with a maximum difference of only 2%. Bioelectromagnetics. 38:474-481, 2017. © 2017 Wiley Periodicals, Inc.

Using ventricular modeling to robustly probe significant deep gray matter pathologies: Application to cerebral palsy.

Understanding the relationships between the structure and function of the brain largely relies on the qualitative assessment of Magnetic Resonance Images (MRIs) by expert clinicians. Automated analysis systems can support these assessments by providing quantitative measures of brain injury. However, the assessment of deep gray matter structures, which are critical to motor and executive function, remains difficult as a result of large anatomical injuries commonly observed in children with Cerebral Palsy (CP). Hence, this article proposes a robust surrogate marker of the extent of deep gray matter injury based on impingement due to local ventricular enlargement on surrounding anatomy. Local enlargement was computed using a statistical shape model of the lateral ventricles constructed from 44 healthy subjects. Measures of injury on 95 age-matched CP patients were used to train a regression model to predict six clinical measures of function. The robustness of identifying ventricular enlargement was demonstrated by an area under the curve of 0.91 when tested against a dichotomised expert clinical assessment. The measures also showed strong and significant relationships for multiple clinical scores, including: motor function (r2 = 0.62, P < 0.005), executive function (r2 = 0.55, P < 0.005), and communication (r2 = 0.50, P < 0.005), especially compared to using volumes obtained from standard anatomical segmentation approaches. The lack of reliance on accurate anatomical segmentations and its resulting robustness to large anatomical variations is a key feature of the proposed automated approach. This coupled with its strong correlation with clinically meaningful scores, signifies the potential utility to repeatedly assess MRIs for clinicians diagnosing children with CP. Hum Brain Mapp 37:3795-3809, 2016. © 2016 Wiley Periodicals, Inc.

Alterations in regional shape on ipsilateral and contralateral cortex contrast in children with unilateral cerebral palsy and are predictive of multiple outcomes.

Congenital brain lesions result in a wide range of cerebral tissue alterations observed in children with cerebral palsy (CP) that are associated with a range of functional impairments. The relationship between injury severity and functional outcomes, however, remains poorly understood. This research investigates the differences in cortical shape between children with congenital brain lesions and typically developing children (TDC) and investigates the correlations between cortical shape and functional outcome in a large cohort of patients diagnosed with unilateral CP. Using 139 structural magnetic resonance images, including 95 patients with clinically diagnosed CP and 44 TDC, cortical segmentations were obtained using a modified expectation maximization algorithm. Three shape characteristics (cortical thickness, curvature, and sulcal depth) were computed within a number of cortical regions. Significant differences in these shape measures compared to the TDC were observed on both the injured hemisphere of children with CP (P < 0.004), as well as on the apparently uninjured hemisphere, illustrating potential compensatory mechanisms in these children. Furthermore, these shape measures were significantly correlated with several functional outcomes, including motor, cognition, vision, and communication (P < 0.012), with three out of these four models performing well on test set validation. This study highlights that cortical neuroplastic effects may be quantified using MR imaging, allowing morphological changes to be studied longitudinally, including any influence of treatment. Ultimately, such approaches could be used for the long term prediction of outcomes and the tailoring of treatment to individuals. Hum Brain Mapp 37:3588-3603, 2016. © 2016 Wiley Periodicals, Inc.

Dielectric properties of dog brain tissue measured in vitro across the 0.3-3 GHz band.

Dielectric properties of dead Greyhound female dogs' brain tissues at different ages were measured at room temperature across the frequency range of 0.3-3 GHz. Measurements were made on excised tissues, in vitro in the laboratory, to carry out dielectric tests on sample tissues. Each dataset for a brain tissue was parametrized using the Cole-Cole expression, and the relevant Cole-Cole parameters for four tissue types are provided. A comparison was made with the database available in literature for other animals and human brain tissue. Results of two types of tissues (white matter and skull) showed systematic variation in dielectric properties as a function of animal age, whereas no significant change related to age was noticed for other tissues. Results provide critical information regarding dielectric properties of animal tissues for a realistic animal head model that can be used to verify the validity and reliability of a microwave head scanner for animals prior to testing on live animals. Bioelectromagnetics. 37:549-556, 2016. © 2016 Wiley Periodicals, Inc.

Modeling of a rotary blood pump.

The accurate representation of rotary blood pumps in a numerical environment is important for meaningful investigation of pump-cardiovascular system interactions. Although numerous models for ventricular assist devices (VADs) have been developed, modeling methods for rotary total artificial hearts (rTAHs) are still required. Therefore, an rTAH prototype was characterized in a steady flow, hydraulic test bench over a wide operational range for pump and hydraulic parameters. In order to develop a generic modeling method, a data-driven modeling approach was chosen. k-Nearest-neighbors, artificial neural networks, and support vector machines (SVMs) were the machine learning approaches evaluated. The best performing parameters for each algorithm were determined via optimization. The resulting multiple-input-multiple-output models were subsequently assessed under identical conditions, and a SVM with a radial basis function kernel was identified as the best performing. The achieved root mean squared errors were 0.03 L/min, 0.06 L/min, and 0.18 W for left and right flow and motor power consumption, respectively. In comparison with existing models for VADs, the flow errors are more than 70% lower. Further advantages of the SVM model are the robustness to measurement noise and the capability to operate outside of the trained parameter range. This proposed modeling method will accelerate further device refinements by providing a more appropriate numerical environment in which to evaluate the pump-cardiovascular system interaction.

A hybrid mock circulation loop for a total artificial heart.

Rotary blood pumps are emerging as a viable technology for total artificial hearts, and the development of physiological control algorithms is accelerated with new evaluation environments. In this article, we present a novel hybrid mock circulation loop (HMCL) designed specifically for evaluation of rotary total artificial hearts (rTAH). The rTAH is operated in the physical domain while all vasculature elements are embedded in the numerical domain, thus combining the strengths of both approaches: fast and easy exchange of the vasculature model together with improved controllability of the pump. Parameters, such as vascular resistance, compliance, and blood volume, can be varied dynamically in silico during operation. A hydraulic-numeric interface creates a real-time feedback loop between the physical and numerical domains. The HMCL uses computer-controlled resistance valves as actuators, thereby reducing the size and number of hydraulic elements. Experimental results demonstrate a stable interaction over a wide operational range and a high degree of flexibility. Therefore, we demonstrate that the newly created design environment can play an integral part in the hydraulic design, control development, and durability testing of rTAHs.

A preliminary investigation into the use of an auditory brainstem response (ABR) simulator for training audiology students in waveform analysis.

OBJECTIVE: To determine if a computer simulation can be used to improve the ability of audiology students to analyse ABR waveforms. DESIGN: A pretest-posttest, quasi-experimental design was used. All participants completed a pretraining examination of their ability to analyse ABR waveforms, eight hours of ABR analysis training over eight weeks using one of three training modes-manual, simulator or combined manual and simulator training, and a posttraining examination of their ability to analyse ABR waveforms. STUDY SAMPLE: Fourteen third-year audiology students (13 female, one male, aged 21 to 22 years) participated in this study. RESULTS: Participants who completed the manual or the combined manual and simulator training achieved significantly higher normalized gain scores on their ABR waveform analysis examinations compared to those who completed the simulator training (p < 0.05). CONCLUSIONS: Our findings suggest that the improvements seen in the ability of these audiology students to analyse ABR waveforms were driven primarily by the manual training. The minimal improvements seen in the students who received the simulator training suggest that face-to-face instruction could be required to enhance the ability of audiology students to analyse ABR waveforms.

Conducting shorter VEP tests to estimate visual acuity via assessment of SNR.

INTRODUCTION: The estimation of visual acuity (VA) via visual evoked potentials (VEP) is a valuable measure for all preverbal and non-verbal subjects whether adults or children. The aim of this study is to introduce a novel technique of VEP acquisition based on estimates of signal-to-noise ratio (SNR) and comparison to a predefined detection threshold. We aim to demonstrate the reduction in total study time without compromising the accuracy of the VEP-determined acuity estimate. METHODS: The VEP-determined acuity of twelve normal subjects was assessed via a spatial frequency (SF) sweep. A pattern reversal checkerboard stimulus utilised SFs ranging from 0.1 to 28 cycles per degree (cpd). Using linear extrapolation and Bland-Altman analysis, VEP-acquired acuity was compared to a conventional Snellen Acuity measurement. An SNR test, Fsp, assessed signal quality to determine the minimum amount of sweep data required for VEP-based VA estimation. RESULTS: VEP acuity estimates correlated strongly (r2=0.91, SD=0.06), leading to a VA limit via extrapolation. Bland-Altman analysis revealed agreement between tests is statistically valid (95% CI -0.11 to 0.42 logMAR). The Fsp statistic indicated SFs 1.3-3.6 cpd yielded Fsp>3.1 within 15 s of acquisition with frequencies>3.6 cpd being sub-threshold. The Kruskal-Wallis statistic compared final Fsp values for SFs as groups, where F=208.82 ranking each frequency, with frequencies>7.2 cpd ranking lowest. DISCUSSION: The Fsp as an SNR measurement shows that rapid, quality-driven clinical tests for VEP-based acuity estimates can be conducted without compromising accuracy.

The audiological health of horn players.

Among orchestral musicians, horn players are one of the most at-risk groups for noise-induced hearing loss (NIHL). To investigate this group further, pure tone audiometry and a 14-item questionnaire were used to assess the hearing health, as well as attitudes and practices regarding hearing conservation, among 142 French horn players attending an international horn conference in Brisbane, Australia. Of this study's French horn players, 11.1% to 22.2%, and 17.7% to 32.9% of those aged ≤40 years, showed some form of hearing loss (corrected for age and gender) typical of NIHL, using conservative versus lenient criteria, respectively. Stepwise multiple regression analyses showed no obvious predictor of hearing loss in this study's participants. Of the 18% of participants who reported using hearing protection, 81% used this protection "sometimes" and 50% used generic, foam, or other inferior forms of protection. Continued efforts to better manage the hearing health of horn players is warranted particularly as any hearing loss will affect a horn player's ability to perform and therefore his or her livelihood. Managing the hearing health of horn players will be challenging, however, with no simple predictor of NIHL loss being identified in this study's sample.

Validation and algorithmic audit of a deep learning system for the detection of proximal femoral fractures in patients in the emergency department: a diagnostic accuracy study.

BACKGROUND: Proximal femoral fractures are an important clinical and public health issue associated with substantial morbidity and early mortality. Artificial intelligence might offer improved diagnostic accuracy for these fractures, but typical approaches to testing of artificial intelligence models can underestimate the risks of artificial intelligence-based diagnostic systems. METHODS: We present a preclinical evaluation of a deep learning model intended to detect proximal femoral fractures in frontal x-ray films in emergency department patients, trained on films from the Royal Adelaide Hospital (Adelaide, SA, Australia). This evaluation included a reader study comparing the performance of the model against five radiologists (three musculoskeletal specialists and two general radiologists) on a dataset of 200 fracture cases and 200 non-fractures (also from the Royal Adelaide Hospital), an external validation study using a dataset obtained from Stanford University Medical Center, CA, USA, and an algorithmic audit to detect any unusual or unexpected model behaviour. FINDINGS: In the reader study, the area under the receiver operating characteristic curve (AUC) for the performance of the deep learning model was 0·994 (95% CI 0·988-0·999) compared with an AUC of 0·969 (0·960-0·978) for the five radiologists. This strong model performance was maintained on external validation, with an AUC of 0·980 (0·931-1·000). However, the preclinical evaluation identified barriers to safe deployment, including a substantial shift in the model operating point on external validation and an increased error rate on cases with abnormal bones (eg, Paget's disease). INTERPRETATION: The model outperformed the radiologists tested and maintained performance on external validation, but showed several unexpected limitations during further testing. Thorough preclinical evaluation of artificial intelligence models, including algorithmic auditing, can reveal unexpected and potentially harmful behaviour even in high-performance artificial intelligence systems, which can inform future clinical testing and deployment decisions. FUNDING: None.

Quantifiable brain atrophy synthesis for benchmarking of cortical thickness estimation methods.

Cortical thickness (CTh) is routinely used to quantify grey matter atrophy as it is a significant biomarker in studying neurodegenerative and neurological conditions. Clinical studies commonly employ one of several available CTh estimation software tools to estimate CTh from brain MRI scans. In recent years, machine learning-based methods emerged as a faster alternative to the main-stream CTh estimation methods (e.g. FreeSurfer). Evaluation and comparison of CTh estimation methods often include various metrics and downstream tasks, but none fully covers the sensitivity to sub-voxel atrophy characteristic of neurodegeneration. In addition, current evaluation methods do not provide a framework for the intra-method region-wise evaluation of CTh estimation methods. Therefore, we propose a method for brain MRI synthesis capable of generating a range of sub-voxel atrophy levels (global and local) with quantifiable changes from the baseline scan. We further create a synthetic test set and evaluate four different CTh estimation methods: FreeSurfer (cross-sectional), FreeSurfer (longitudinal), DL+DiReCT and HerstonNet. DL+DiReCT showed superior sensitivity to sub-voxel atrophy over other methods in our testing framework. The obtained results indicate that our synthetic test set is suitable for benchmarking CTh estimation methods on both global and local scales as well as regional inter-and intra-method performance comparison.

On chirp stimuli and neural synchrony in the suprathreshold auditory brainstem response.

The chirp-evoked ABR has been regarded as a more synchronous response than the click-evoked ABR, referring to the belief that the chirp stimulates lower-, mid-, and higher-frequency regions of the cochlea simultaneously. In this study a variety of tools were used to analyze the synchronicity of ABRs evoked by chirp- and click-stimuli at 40 dB HL in 32 normal hearing subjects aged 18 to 55 years (mean=24.8 years, SD=7.1 years). Compared to the click-evoked ABRs, the chirp-evoked ABRs showed larger wave V amplitudes, but an absence of earlier waves in the grand averages, larger wave V latency variance, smaller FFT magnitudes at the higher component frequencies, and larger phase variance at the higher component frequencies. These results strongly suggest that the chirp-evoked ABRs exhibited less synchrony than the click-evoked ABRs in this study. It is proposed that the temporal compensation offered by chirp stimuli is sufficient to increase neural recruitment (as measured by wave V amplitude), but that destructive phase interactions still exist along the cochlea partition, particularly in the low frequency portions of the cochlea where more latency jitter is expected. The clinical implications of these findings are discussed.

Spectral and synchrony differences in auditory brainstem responses evoked by chirps of varying durations.

The chirp-evoked ABR has been termed a more synchronous response, referring to the fact that rising-frequency chirp stimuli theoretically compensate for temporal dispersions down the basilar membrane. This compensation is made possible by delaying the higher frequency content of the stimulus until the lower frequency traveling waves are closer to the cochlea apex. However, it is not yet clear how sensitive this temporal compensation is to variation in the delay interval. This study analyzed chirp- and click-evoked ABRs at low intensity, using a variety of tools in the time, frequency, and phase domains, to measure synchrony in the response. Additionally, this study also examined the relationship between chirp sweep rate and response synchrony by varying the delay between high- and low-frequency portions of chirp stimuli. The results suggest that the chirp-evoked ABRs in this study exhibited more synchrony than the click-evoked ABRs and that slight gender-based differences exist in the synchrony of chirp-evoked ABRs. The study concludes that a tailoring of chirp parameters to gender may be beneficial in pathologies that severely affect neural synchrony, but that such a customization may not be necessary in routine clinical applications.

Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI.

Previous studies on computer aided detection/diagnosis (CAD) in 4D breast magnetic resonance imaging (MRI) usually regard lesion detection, segmentation and characterization as separate tasks, and typically require users to manually select 2D MRI slices or regions of interest as the input. In this work, we present a breast MRI CAD system that can handle 4D multimodal breast MRI data, and integrate lesion detection, segmentation and characterization with no user intervention. The proposed CAD system consists of three major stages: region candidate generation, feature extraction and region candidate classification. Breast lesions are firstly extracted as region candidates using the novel 3D multiscale morphological sifting (MMS). The 3D MMS, which uses linear structuring elements to extract lesion-like patterns, can segment lesions from breast images accurately and efficiently. Analytical features are then extracted from all available 4D multimodal breast MRI sequences, including T1-, T2-weighted and DCE sequences, to represent the signal intensity, texture, morphological and enhancement kinetic characteristics of the region candidates. The region candidates are lastly classified as lesion or normal tissue by the random under-sampling boost (RUSboost), and as malignant or benign lesion by the random forest. Evaluated on a breast MRI dataset which contains a total of 117 cases with 141 biopsy-proven lesions (95 malignant and 46 benign lesions), the proposed system achieves a true positive rate (TPR) of 0.90 at 3.19 false positives per patient (FPP) for lesion detection and a TPR of 0.91 at a FPP of 2.95 for identifying malignant lesions without any user intervention. The average dice similarity index (DSI) is0.72±0.15for lesion segmentation. Compared with previously proposed lesion detection, detection-segmentation and detection-characterization systems evaluated on the same breast MRI dataset, the proposed CAD system achieves a favourable performance in breast lesion detection and characterization.

Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI.

We propose a new method for breast cancer screening from DCE-MRI based on a post-hoc approach that is trained using weakly annotated data (i.e., labels are available only at the image level without any lesion delineation). Our proposed post-hoc method automatically diagnosis the whole volume and, for positive cases, it localizes the malignant lesions that led to such diagnosis. Conversely, traditional approaches follow a pre-hoc approach that initially localises suspicious areas that are subsequently classified to establish the breast malignancy - this approach is trained using strongly annotated data (i.e., it needs a delineation and classification of all lesions in an image). We also aim to establish the advantages and disadvantages of both approaches when applied to breast screening from DCE-MRI. Relying on experiments on a breast DCE-MRI dataset that contains scans of 117 patients, our results show that the post-hoc method is more accurate for diagnosing the whole volume per patient, achieving an AUC of 0.91, while the pre-hoc method achieves an AUC of 0.81. However, the performance for localising the malignant lesions remains challenging for the post-hoc method due to the weakly labelled dataset employed during training.

Author Correction: Why rankings of biomedical image analysis competitions should be interpreted with care.

In the original version of this Article the values in the rightmost column of Table 1 were inadvertently shifted relative to the other columns. This has now been corrected in the PDF and HTML versions of the Article.

Estimation of neuronal firing rates with the three-state biological point process model.

In the subcortex of the human brain, neuronal firing events are stochastic and the inter-arrival times of action potentials (APs) are highly irregular. It has been shown that stimulation of the subthalamic nucleus (STN), a small subcortical structure located within the basal ganglia, can help ameliorate the motor symptoms associated with Parkinson's disease (PD). However, success of image guided stereotactic surgery is reliant upon the refinement of the anatomic target (in this case the STN) based on micro-electrode recordings (MERs) of background activity and firing rate. In practice MERs must be analysed on-line and in real-time. Currently, the most common method of performing on-line MER analysis is a manual thresholding procedure. However, this is subjective in nature and often complicated by the presence of variable amounts of background noise. Therefore, in this paper, we present an automated adaptive thresholding technique, based on a modified 'top-hat' operator, which detects APs exceeding the local background activity. We then go on to model these inter-arrival times using a coupled Poisson process that provides improved estimates of both inter-burst and intra-burst neuronal firing activity in the STN.