Comparison of 2D and autostereoscopic 3D visualization during mixed reality simulation.

PURPOSE: In general minimally invasive surgical procedures, surgeons are tied to 2D visualization, leading to the loss of depth perception. This can lead to large mental load for the surgeons and may be responsible for the long learning curve. To restore the sense of depth, this study investigated the use and benefits of an autostereoscopic (3D) display during a simulated laparoscopic task. METHODS: A mixed reality simulator was developed for comparing the performance of participants while using 2D and autostereoscopic 3D visualization. An electromagnetic sensor was mounted on a physical instrument, and its pose was mapped to the virtual instrument. The virtual scene was developed using Simulation Open Framework Architecture (SOFA). Finite element modeling was used to calculate interaction forces, which were then mapped to visual soft tissue deformation. RESULTS: Ten non-expert participants completed a virtual laparoscopic task, where the subjects were asked to contact eighteen target areas distributed on the surface of the vagina, both in 2D and 3D. Results showed an improvement with 3D vision in task completion time (-16%), total traveled distance (-25%) and errors made (-14%). There was no difference in the average contact forces between the vagina and the instrument. Only the difference in time and forces were shown to be statistically significant. CONCLUSION: Overall, autostereoscopic 3D showed superiority over conventional 2D visualization. The traveled trajectory increased in 2D as the instrument was retracted more between the targets to avoid contact. The 2D and 3D deformation upon contact seems not to contribute differently to force perception. However, the participants only had visual feedback, but no haptic feedback. Therefore, it could be interesting to include haptic feedback in a future study.

Can Multispectral Dermoscopy Help In Distinguishing Blue Color?

INTRODUCTION: The interpretation of colors is essential in the dermoscopic evaluation of skin lesions. The same blue color on white dermoscopy may indicate blood or pigment deep in the dermis. Contrary to white dermoscopy, multispectral dermoscopy uses different wavelengths of light to illuminate a lesion and is able to decompose the dermoscopic image into individual maps that allow to more clearly visualize specific skin structures such as pigment distribution (pigment map) and vasculature (blood map). These maps are called skin parameter maps. OBJECTIVES: The aim of this research is to investigate whether skin parameter maps can be used to objectively identify and distinguish the presence of pigment and blood, by using blue naevi and angiomas as models for respectively pigment and blood. METHODS: We retrospectively analyzed 24 blue naevi and 79 angiomas. The skin parameter maps of each of the lesions were independently reviewed by 3 expert dermoscopists, in the absence of the regular white-light dermoscopic image. RESULTS: All the observers provided high levels of diagnostic accuracy for blue naevus and angioma based on skin parameter maps alone, and the dermoscopic diagnosis was considered substantially reliable because of the 79% of diagnostic K agreement. Percentages of blue naevi and angiomas that showed respectively deep pigment and blood were very high at 95.8% and 97.5%. There was a percentage of lesions that counterintuitively showed blood in blue naevi (37.5%) and deep pigment in angiomas (28.8%). CONCLUSIONS: Skin parameter maps based on multispectral images can help to objectify the presence of deep pigment or blood in blue naevi and angiomas. The application of these skin parameter maps could help in the differential diagnosis between pigmented and vascular lesions.

Preoperative assessment of cutaneous melanoma thickness by multispectral dermoscopy.

Preoperative assessment of Breslow thickness by means of sonography and clinical and dermoscopic criteria in white light dermoscopy has been reported, but up until now, the use of multispectral dermoscopy has not been investigated. Aim of this research is to determine whether multispectral dermoscopy and more specifically pigment maps can be used as a predictive marker for Breslow thickness in melanoma. Pigment maps are generated in real time from multispectral dermoscopic images and help to visualize the presence of pigment in a lesion. Multispectral images of 110 melanomas were collected, using a digital handheld multispectral dermatoscope, and assessed independently by five observers for the presence or absence of deep pigment compared with the surrounding skin. According to histopathological examination, the mean Breslow thickness of all 110 melanomas was 1.04 mm (ranging from 0.1 to 14 mm). The group of melanomas where deep pigment was visualized on the multispectral image (n = 78) had a significantly higher Breslow thickness (1.19 mm) than the group where no deep pigment was observed (n = 32, mean Breslow 0.68 mm) (P = 0.025). This study is unique in preoperative assessment of tumour thickness by means of multispectral dermoscopy. Our data indicate that the presence of deep pigment as visualized in digital dermoscopic skin parameter maps identifies a group of thicker melanomas. Further prospective research is needed to validate these pigment maps, generated by multispectral dermoscopy as a measure to predict invasiveness in melanoma.

Motion and viewing analysis during minimally invasive surgery for autostereoscopic visualization.

PURPOSE: Autostereoscopic 3D visualization (ASV) forms a potentially appealing alternative to stereoscopic 3D displays to help surgeons regain depth perception during minimally invasive surgery (MIS). However, the feasibility of using single-viewer ASV has not yet been demonstrated in a clinical context. The purpose of the study is to analyze the current surgical workflow and display usage and assess the potential for using ASV in MIS applications. Additionally, the study seeks to acquire a better understanding of key design requirements, such as the eye-tracking performance and the lenticular lens 3D workspace. METHODS: Two types of gynecologic interventions were investigated. A vision-based tracking system was developed, consisting of depth cameras mounted on the displays and ArUco markers placed on the hair caps of clinicians and the wall of the operating room. This allowed simultaneous tracking of the pose of operating staff and displays. RESULTS: Overall 20 surgeries were recorded, where 4 clinicians operated using 3 displays. Users were typically standing at a mean distance of 1900 mm in a range from to 1200 to 2300 mm from the display. Left-right motion was from - 600 to 658 mm. Clinicians stood on average 1000 mm from each other. The head roll angle was below 16[Formula: see text]. CONCLUSION: Surgeons were looking predominantly (99%) to the same display. Observations took place from fairly well-defined places and with sufficient potential to differentiate between clinicians, suggesting that single-viewer ASV would be feasible.

In-depth Retrospective Review of Originally Negative Screening Mammograms from Women with Confirmed Breast Cancer.

Objectives: We aim to contribute to the assessment of the screening performance in Flanders (Belgium) and to identify valuable mammograms for subsequent studies and training. Materials and Methods: Initially negative prior screening mammograms (sMx) of 210 women with confirmed breast cancer detected by the Flemish screening programme between 2011-2013 were reviewed by a highly experienced radiologist. The review of the prior sMx was performed in three steps: 1) only prior mammograms available; 2) with index sMx (=subsequent positive sMx) present; 3) with index sMx and clinical information present. Results: The radiological review yielded 94 (45%) mammograms 'without suspicious lesions', 77 (37%) 'with minimal signs in at least one breast', and 39 (19%) 'with clearly visible tumours'. In univariate analyses, the reclassification of prior sMx was significantly associated with the date of the prior sMx, the need for a third reader for arbitration, image quality and the detector system used (computed radiography versus direct readout digital radiography), and it was not associated with the interval between screening rounds, age at prior sMx, breast density, or tumour characteristics (

Ethical implications of AI in robotic surgical training: A Delphi consensus statement.

CONTEXT: As the role of AI in healthcare continues to expand there is increasing awareness of the potential pitfalls of AI and the need for guidance to avoid them. OBJECTIVES: To provide ethical guidance on developing narrow AI applications for surgical training curricula. We define standardised approaches to developing AI driven applications in surgical training that address current recognised ethical implications of utilising AI on surgical data. We aim to describe an ethical approach based on the current evidence, understanding of AI and available technologies, by seeking consensus from an expert committee. EVIDENCE ACQUISITION: The project was carried out in 3 phases: (1) A steering group was formed to review the literature and summarize current evidence. (2) A larger expert panel convened and discussed the ethical implications of AI application based on the current evidence. A survey was created, with input from panel members. (3) Thirdly, panel-based consensus findings were determined using an online Delphi process to formulate guidance. 30 experts in AI implementation and/or training including clinicians, academics and industry contributed. The Delphi process underwent 3 rounds. Additions to the second and third-round surveys were formulated based on the answers and comments from previous rounds. Consensus opinion was defined as ≥ 80% agreement. EVIDENCE SYNTHESIS: There was 100% response from all 3 rounds. The resulting formulated guidance showed good internal consistency, with a Cronbach alpha of >0.8. There was 100% consensus that there is currently a lack of guidance on the utilisation of AI in the setting of robotic surgical training. Consensus was reached in multiple areas, including: 1. Data protection and privacy; 2. Reproducibility and transparency; 3. Predictive analytics; 4. Inherent biases; 5. Areas of training most likely to benefit from AI. CONCLUSIONS: Using the Delphi methodology, we achieved international consensus among experts to develop and reach content validation for guidance on ethical implications of AI in surgical training. Providing an ethical foundation for launching narrow AI applications in surgical training. This guidance will require further validation. PATIENT SUMMARY: As the role of AI in healthcare continues to expand there is increasing awareness of the potential pitfalls of AI and the need for guidance to avoid them.In this paper we provide guidance on ethical implications of AI in surgical training.

Enhanced visualization of blood and pigment in multispectral skin dermoscopy.

BACKGROUND AND OBJECTIVES: Dermoscopy has proven its value in the diagnosis of skin cancer and, therefore, is well established in daily dermatology practice. Up until now, analogue white light dermoscopy is the standard. Multispectral dermoscopy is based on illumination of the skin with narrowband light sources with different wavelengths. Each of these wavelengths is differently absorbed by skin chromophores, such as pigment or (de)oxygenated blood. Multispectral dermoscopy could be a way to enhance the visualization of vasculature and pigment. We illustrate possible additional information by such "skin parameter maps" in some cases of basal cell carcinoma and Bowen's disease. METHODS: Using a new digital multispectral dermatoscope, skin images at multiple wavelengths are collected from different types of skin lesions. These particular images together with the knowledge on skin absorption properties, result in so called "skin parameter maps". RESULTS: A "pigment contrast map," which shows the relative concentration of primarily pigment, and a "blood contrast map" which shows the relative concentration of primarily blood were created. Especially, the latter is of importance in diagnosing keratinocyte skin cancer hence vascular structures are a characteristic feature, as further illustrated in the study. CONCLUSIONS: Skin parameter maps based on multispectral images can give better insight in the inner structures of lesions, especially in lesions with characteristic blood vessels such as Bowen's disease and basal cell carcinoma. Skin parameter maps can be used complementary to regular dermoscopy and could potentially facilitate diagnosing skin lesions.

Location- and lesion-dependent estimation of mammographic background tissue complexity.

We specify a notion of perceived background tissue complexity (BTC) that varies with lesion shape, lesion size, and lesion location in the image. We propose four unsupervised BTC estimators based on: perceived pre and postlesion similarity of images, lesion border analysis (LBA; conspicuous lesion should be brighter than its surround), tissue anomaly detection, and local energy. The latter two are existing methods adapted for location- and lesion-dependent BTC estimation. For evaluation, we ask human observers to measure BTC (threshold visibility amplitude of a given lesion inserted) at specified locations in a mammogram. As expected, both human measured and computationally estimated BTC vary with lesion shape, size, and location. BTCs measured by different human observers are correlated ([Formula: see text]). BTC estimators are correlated to each other ([Formula: see text]) and less so to human observers ([Formula: see text]). With change in lesion shape or size, LBA estimated BTC changes in the same direction as human measured BTC. Proposed estimators can be generalized to other modalities (e.g., breast tomosynthesis) and used as-is or customized to a specific human observer, to construct BTC-aware model observers with applications, such as optimization of contrast-enhanced medical imaging systems and creation of a diversified image dataset with characteristics of a desired population.

Color standard display function: A proposed extension of DICOM GSDF.

PURPOSE: Color images are being used more in medical imaging for a broad range of modalities and applications. While in the past, color was mostly used for annotations, today color is also widely being used for diagnostic purposes. Surprisingly enough, there is no agreed upon standard yet that describes how color medical images need to be visualized and how calibration and quality assurance of color medical displays need to be performed. This paper proposes color standard display function (CSDF) which is an extension of the DICOM GSDF standard toward color. CSDF defines how color medical displays need to be calibrated and how QA can be performed to obtain perceptually linear behavior not only for grayscale but also for color. METHODS: The proposed CSDF algorithm uses DICOM GSDF calibration as a starting point and subsequently uses a color visual difference metric to redistribute colors in order to obtain perceptual linearity not only for the grayscale behavior but also for the color behavior. A clear calibration and quality assurance algorithm is defined and is validated on a wide range of different display systems. RESULTS: A detailed description of the proposed CSDF calibration and quality assurance algorithms is provided. These algorithms have been tested extensively on three types of display systems: consumer displays, professional displays, and medical grade displays. Test results are reported both for the calibration algorithm as well as for the quantitative and visual quality assurance methods. The tests confirm that the described algorithm generates consistent results and is able to increase perceptual linearity for color and grayscale visualization. Moreover the proposed algorithms are working well on a wide range of display systems. CONCLUSIONS: CSDF has been proposed as an extension of the DICOM GSDF standard toward color. Calibration and QA algorithms for CSDF have been described in detail. The proposed algorithms have been tested on several types of display systems and the results confirm that CSDF largely increases the perceptual linearity of visualized colors, while at the same time remaining compliant with DICOM GSDF.

Consistency and standardization of color in medical imaging: a consensus report.

This article summarizes the consensus reached at the Summit on Color in Medical Imaging held at the Food and Drug Administration (FDA) on May 8-9, 2013, co-sponsored by the FDA and ICC (International Color Consortium). The purpose of the meeting was to gather information on how color is currently handled by medical imaging systems to identify areas where there is a need for improvement, to define objective requirements, and to facilitate consensus development of best practices. Participants were asked to identify areas of concern and unmet needs. This summary documents the topics that were discussed at the meeting and recommendations that were made by the participants. Key areas identified where improvements in color would provide immediate tangible benefits were those of digital microscopy, telemedicine, medical photography (particularly ophthalmic and dental photography), and display calibration. Work in these and other related areas has been started within several professional groups, including the creation of the ICC Medical Imaging Working Group.

Increasing the number of gray shades in medical display systems--how much is enough?

Medical images produced by x-ray detectors, computed tomography (CT) scanners, and other modalities typically contain between 12-16 bits/pixel, which corresponds to 4,096-65,536 shades of gray. On the other hand, we see that these images are visualized by means of medical displays that have much lower available number of gray shades. For a long time medical LCDs only supported 8 bits or 256 shades of gray per pixel. With the introduction of medical displays optimized for mammography, the available number of gray scales increased to 1,024. Recently, several manufacturers announced new display systems with higher bit depth. Because higher bit depth often directly results in higher display cost, it is a logical question to ask if this is required or even useful at all. This paper will give an answer by investigating several aspects such as limitations of the human visual system, digital imaging and communication in medicine grayscale standard display function calibration, and characteristics of medical LCDs.

Defective pixels in medical LCD displays: problem analysis and fundamental solution.

Over the past few years, traditional CRT displays have gradually been replaced by active matrix LCD displays. Each pixel in an LCD display has its own individual transistor that controls the transmittance of that pixel. Occasionally, these individual transistors will short or malfunction, resulting in a defective pixel that always shows the same brightness. This article shows how defective LCD pixels can interfere with subtle features in medical images. A defective pixel affects a broad area around it therefore possibly reducing the quality of diagnosis specifically for highly demanding applications such as mammography. A specialized image processing algorithm provides an innovative solution making these defects completely invisible and recovers information from the defect so the radiologist perceives the medical image correctly.

Solution for nonuniformities and spatial noise in medical LCD displays by using pixel-based correction.

Liquid crystal displays (LCD) are rapidly replacing cathode ray tube displays (CRT) for medical imaging. LCD technology has improved significantly in the last few years and has important advantages over CRT. However, there are still some aspects of LCD that raise questions as to the usefulness of liquid crystal displays for very subtle clinical diagnosis such as mammography. One drawback of modern LCD displays is the existence of spatial noise expressed as measurable stationary differences in the behavior of individual pixels. This type of noise can be described as a random stationary image superposed on top of the medical image being displayed. It is obvious that this noise image can make subtle structures invisible or add nonexistent patterns to the medical image. In the first case, subtle abnormalities in the medical image could remain undetected, whereas in the second case, it could result into a false positive. This paper describes a method to characterize the spatial noise present in high-resolution medical displays and a technique to solve the problem. A medical display with built-in compensation for the spatial noise at pixel level was developed and improved image quality is demonstrated.