Assessment of the potential radiation hazards posed by Nubian sandstone, Egypt.

The study found that the activity concentrations of the radionuclides 238U, 232Th and 40K in the sandstone are 32 ± 13, 29.6 ± 12.2, and 132.6 ± 86.4 Bq kg-1, respectively. These values are lower than the reported worldwide limits of 33, 45, and 412 Bq kg-1. According to the present study, the absorbed dose rate (Dair), the annual effective dose, and the excess life time cancer were all found to be below the worldwide mean. Pearson correlation, PCA, and HCA were used to analyze the data and identify patterns in the relationship between radionuclides and radiological hazards. A statistical analysis of the sandstones showed that the radioactive elements 238U, 232Th and 40K are the main contributors to the radioactive risk. The study suggests that the sandstone is safe to use. The levels of radioactivity are not high enough to pose a risk to human health.

Excess Lifetime Cancer Risk Associated with Granite Bearing Radioactive Minerals and Valuable Metals, Monqul Area, North Eastern Desert, Egypt.

The present work is concerned with assessing the cancer risk contributed by the studied granite types including valuable metals, such as Cu, Au, and Ba mineralization, as well as radioactive-bearing mineralization, such as monazite and zircon, in south Monqul at Wadi Makhrag El Ebel, north Eastern Desert, Egypt. The mineralization analyses illustrated that copper mineralization containing chrysocolla and tenorite minerals were restricted to the alteration zone, especially (argillic, phyllic, and propylitic) in monzogranite. However, barite veinlets had an ENE-WSW trend, while gold mineralization was confined to quartz veins having NE-SW trends. Monazite and zircon are radioactive-bearing minerals recorded in monzogranite causing high radioactive zones in south Monqul. The radionuclide activity concentrations were detected in the studied monzogranites. The mean values of AU (103 ± 91 Bq kg-1), ATh (78 ± 19 Bq kg-1), and AK (1484 ± 334 Bq kg-1) in the monzogranite samples were higher than the recommended worldwide average. The change in radioactive-transporting minerals found inside granite faults caused the high amounts of radioactivity seen in the samples. Due to the monzogranites being applied in building materials, the radiological hazards were assessed by calculating risk indices such as annual effective dose (AED) and excess lifetime cancer risk (ELCR). The acceptable limit for the ELCR readings was surpassed. As a result, the investigated monzogranite samples are not suitable for use in infrastructure materials.

Dynamic detection and reversal of myocardial ischemia using an artificially intelligent bioelectronic medicine.

Myocardial ischemia is spontaneous, frequently asymptomatic, and contributes to fatal cardiovascular consequences. Importantly, myocardial sensory networks cannot reliably detect and correct myocardial ischemia on their own. Here, we demonstrate an artificially intelligent and responsive bioelectronic medicine, where an artificial neural network (ANN) supplements myocardial sensory networks, enabling reliable detection and correction of myocardial ischemia. ANNs were first trained to decode spontaneous cardiovascular stress and myocardial ischemia with an overall accuracy of ~92%. ANN-controlled vagus nerve stimulation (VNS) significantly mitigated major physiological features of myocardial ischemia, including ST depression and arrhythmias. In contrast, open-loop VNS or ANN-controlled VNS following a caudal vagotomy essentially failed to reverse cardiovascular pathophysiology. Last, variants of ANNs were used to meet clinically relevant needs, including interpretable visualizations and unsupervised detection of emerging cardiovascular stress. Overall, these preclinical results suggest that ANNs can potentially supplement deficient myocardial sensory networks via an artificially intelligent bioelectronic medicine system.

Natural radiological characterization at the Gabal El Seila region (Egypt).

Stream sediment is a useful raw material used for building construction, mostly used in the desert parts of the world. Such sediment is a Naturally Occurring Radioactive Material (NORM), and, hence, it requires a radiological characterization to be used. This work aims to study the natural radioactivity in fifty points distributed in surface of stream sediments in the area of Gabal El Seila region, south-eastern desert of Egypt, since there is a lack of information about the radioactivity levels of the sediment samples from such recent growing interest area. The activity concentration of 238U, 232Th and 4 K natural radionuclides using a portable RS-230 γ-ray spectrometer were determined. Mean values are 38.51 ± 10.83, 33.35 ± 8.82, 659.18 ± 110.87 Bq/kg for 238U, 232Th, 4 K respectively. Radiological hazard indexes were computed and compared with the UNSCEAR and other worldwide ranges. All the results are statistically presented and discussed. They show that no significant radiation hazard coming from the studied area, with the most values lower than international recommended limits. The achievements of the present study fall within the measurements of natural environmental radiation in an unexplored area of great interest being a desert. The obtained results can be used as database for future research, and as tool for radiological awareness in the use of sediments as raw material.

SLAM in Dynamic Environments: A Deep Learning Approach for Moving Object Tracking Using ML-RANSAC Algorithm.

The important problem of Simultaneous Localization and Mapping (SLAM) in dynamic environments is less studied than the counterpart problem in static settings. In this paper, we present a solution for the feature-based SLAM problem in dynamic environments. We propose an algorithm that integrates SLAM with multi-target tracking (SLAMMTT) using a robust feature-tracking algorithm for dynamic environments. A novel implementation of RANdomSAmple Consensus (RANSAC) method referred to as multilevel-RANSAC (ML-RANSAC) within the Extended Kalman Filter (EKF) framework is applied for multi-target tracking (MTT). We also apply machine learning to detect features from the input data and to distinguish moving from stationary objects. The data stream from LIDAR and vision sensors are fused in real-time to detect objects and depth information. A practical experiment is designed to verify the performance of the algorithm in a dynamic environment. The unique feature of this algorithm is its ability to maintain tracking of features even when the observations are intermittent whereby many reported algorithms fail in such situations. Experimental validation indicates that the algorithm is able to perform consistent estimates in a fast and robust manner suggesting its feasibility for real-time applications.

Liquid biopsy using the nanotube-CTC-chip: capture of invasive CTCs with high purity using preferential adherence in breast cancer patients.

In this paper, we report the development of the nanotube-CTC-chip for isolation of tumor-derived epithelial cells (circulating tumor cells, CTCs) from peripheral blood, with high purity, by exploiting the physical mechanisms of preferential adherence of CTCs on a nanotube surface. The nanotube-CTC-chip is a new 76-element microarray technology that combines carbon nanotube surfaces with microarray batch manufacturing techniques for the capture and isolation of tumor-derived epithelial cells. Using a combination of red blood cell (RBC) lysis and preferential adherence, we demonstrate the capture and enrichment of CTCs with a 5-log reduction of contaminating WBCs. EpCAM negative MDA-MB-231/luciferase-2A-green fluorescent protein (GFP) cells were spiked in the blood of wild mice and enriched using an RBC lysis protocol. The enriched samples were then processed using the nanotube-CTC-chip for preferential CTC adherence on the nanosurface and counting the GFP cells yielded anywhere from 89% to 100% capture from the droplets. Electron microscopy (EM) studies showed focal adhesion with filaments from the cell body to the nanotube surface. We compared the nanotube preferential adherence to collagen adhesion matrix (CAM) scaffolding, reported as a viable strategy for CTC capture in patients. The CAM scaffolding on the device surface yielded 50% adherence with 100% tracking of cancer cells (adhered vs. non-adhered) versus carbon nanotubes with >90% adherence and 100% tracking for the same protocol. The nanotube-CTC-chip successfully captured CTCs in the peripheral blood of breast cancer patients (stage 1-4) with a range of 4-238 CTCs per 8.5 ml blood or 0.5-28 CTCs per ml. CTCs (based on CK8/18, Her2, EGFR) were successfully identified in 7/7 breast cancer patients, and no CTCs were captured in healthy controls (n = 2). CTC enumeration based on multiple markers using the nanotube-CTC-chip enables dynamic views of metastatic progression and could potentially have predictive capabilities for diagnosis and treatment response.

Publisher Correction: Exfoliated WS2-Nafion Composite based Electromechanical Actuators.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Publisher Correction: Exfoliated WS2-Nafion Composite based Electromechanical Actuators.

A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.

Variation in the use of laparoscopy with inguinal hernia repairs in a sample of pediatric patients at children's hospitals.

INTRODUCTION/BACKGROUND: Metachronous contralateral inguinal hernias (MCH) occur in approximately 10% of pediatric patients following unilateral inguinal hernia repairs (UIHR). Laparoscopic evaluation of the contralateral internal ring is a method of identifying high-risk individuals for prophylactic contralateral exploration and repair. OBJECTIVE: The objective of this study was to assess variation in utilization of diagnostic laparoscopy, and report costs associated with the evaluation of a contralateral patent processus vaginalis during hernia repair in pediatric hospitals. STUDY DESIGN: The Pediatric Health Information System database was searched to identify outpatient surgical encounters for pediatric patients with a diagnosis of inguinal hernia during a 1-year period (2014). Records were identified that contained diagnostic codes for unilateral or bilateral inguinal hernia in combination with a procedure code for open hernia repair with or without diagnostic laparoscopy. RESULTS: After exclusions there were 3952 hernia repairs performed at 30 hospitals; median age was 4 years (IQR 1-7), 78.8% were male, and 64.9% Caucasian. Three-quarters (76.7%) had UIHR, 8.6% had unilateral repairs with laparoscopy (UIHRL), 12.2% had bilateral inguinal hernia repairs (BIHR), and 2.4% had bilateral repairs with laparoscopy (BIHRL). Where laparoscopy was used, 78% resulted in a unilateral repair and 22% in a bilateral procedure. The percent of patients undergoing laparoscopy varied from 0 to 57% among hospitals, and 0-100% among surgeons. Pediatric surgeons were more than three times more likely to perform a diagnostic laparoscopy compared with pediatric urologists. Median adjusted costs were $2298 (IQR 1659-2955) for UIHR, $2713 (IQR 1873-3409) for UIHRL, $2752 (IQR 2230-3411) for BIHR, and $2783 (IQR 2233-3453) for BIHRL. Median costs varied over two-fold among hospitals ($1310-4434), and over four-fold among surgeons ($948-5040). DISCUSSION: Data suggested that <10% of patients with clinically unilateral inguinal hernias developed MCH. A negative diagnostic laparoscopy ensured that 0.9-1.31% developed MCH. However, up to 30% of patients underwent contralateral exploration/repair when diagnostic laparoscopy was used. The current study found increased costs associated with the use of laparoscopy, with considerable variation in costs among surgeons and hospitals. These data elucidate competing financial and clinical consequences associated with the use of diagnostic laparoscopy with clinically unilateral hernias. CONCLUSIONS: Variation existed in the use of laparoscopy during inguinal hernia repairs and associated costs within the current sample from children's hospitals in the United States. The additional costs of laparoscopic evaluation must be considered against the clinical utility and therapeutic consequences of identifying individuals with a higher risk of metachronous contralateral inguinal hernia.

Hypercalcaemia: A portent of sarcoidosis in cystic fibrosis.

The coexistence of cystic fibrosis (CF) and sarcoidosis is rare. We report a 22-year-old male cystic fibrosis patient who presented multiple times to the Sultan Qaboos University Hospital, Muscat, Oman, in 2013. He was diagnosed with non-parathyroid-related hypercalcaemia and anterior uveitis, while computed tomography revealed mediastinal and abdominal lymphadenopathy and mild hepatosplenomegaly. These findings, in addition to the presence of calciuria and a high angiotensin-converting enzyme (ACE) level, confirmed a clinical diagnosis of sarcoidosis. The patient responded well to treatment with oral prednisolone which, over the course of two years, resulted in the near-complete resolution of parenchymal nodular infiltrates, regression of hilar lymphadenopathy, resolution of hypercalcaemia and the normalisation of his ACE levels. Diagnosing pulmonary sarcoidosis in CF can be challenging as most adult patients already have extensive lung disease. Physicians should be aware that hypercalcaemia may be an early manifestation of sarcoidosis in such cases.

Exfoliated WS2-Nafion Composite based Electromechanical Actuators.

The ability to convert electrical energy into mechanical motion is of significant interest in many energy conversion technologies. Here, we demonstrate the first liquid phase exfoliated WS2-Nafion nanocomposite based electro-mechanical actuators. Highly exfoliated layers of WS2 mixed with Nafion solution, solution cast and doped with Li+ was studied as electromechanical actuators. Resonant Raman spectroscopy, X-ray photo-electron-spectroscopy, differential scanning calorimetry, dynamic mechanical analysis, and AC impedance spectroscopy were used to study the structure, photoluminescence, water uptake, mechanical and electromechanical actuation properties of the exfoliated nanocomposites. A 114% increase in elastic modulus (dry condition), 160% increase in proton conductivity, 300% increase in water uptake, cyclic strain amplitudes of ~0.15% for 0.1 Hz excitation frequency, tip displacements greater than nanotube-Nafion and graphene-Nafion actuators and continuous operation for more than 5 hours is observed for TMD-Nafion actuators. The mechanism behind the increase in water uptake is a result of oxygen atoms occupying the vacancies in the hydrophilic exfoliated flakes and subsequently bonding with water, not possible in Nafion composites based on carbon nanotube and graphene.

Evaluation of Three Algorithms for the Segmentation of Overlapping Cervical Cells.

In this paper, we introduce and evaluate the systems submitted to the first Overlapping Cervical Cytology Image Segmentation Challenge, held in conjunction with the IEEE International Symposium on Biomedical Imaging 2014. This challenge was organized to encourage the development and benchmarking of techniques capable of segmenting individual cells from overlapping cellular clumps in cervical cytology images, which is a prerequisite for the development of the next generation of computer-aided diagnosis systems for cervical cancer. In particular, these automated systems must detect and accurately segment both the nucleus and cytoplasm of each cell, even when they are clumped together and, hence, partially occluded. However, this is an unsolved problem due to the poor contrast of cytoplasm boundaries, the large variation in size and shape of cells, and the presence of debris and the large degree of cellular overlap. The challenge initially utilized a database of 16 high-resolution ( ×40 magnification) images of complex cellular fields of view, in which the isolated real cells were used to construct a database of 945 cervical cytology images synthesized with a varying number of cells and degree of overlap, in order to provide full access of the segmentation ground truth. These synthetic images were used to provide a reliable and comprehensive framework for quantitative evaluation on this segmentation problem. Results from the submitted methods demonstrate that all the methods are effective in the segmentation of clumps containing at most three cells, with overlap coefficients up to 0.3. This highlights the intrinsic difficulty of this challenge and provides motivation for significant future improvement.

Clinically-inspired automatic classification of ovarian carcinoma subtypes.

CONTEXT: It has been shown that ovarian carcinoma subtypes are distinct pathologic entities with differing prognostic and therapeutic implications. Histotyping by pathologists has good reproducibility, but occasional cases are challenging and require immunohistochemistry and subspecialty consultation. Motivated by the need for more accurate and reproducible diagnoses and to facilitate pathologists' workflow, we propose an automatic framework for ovarian carcinoma classification. MATERIALS AND METHODS: Our method is inspired by pathologists' workflow. We analyse imaged tissues at two magnification levels and extract clinically-inspired color, texture, and segmentation-based shape descriptors using image-processing methods. We propose a carefully designed machine learning technique composed of four modules: A dissimilarity matrix, dimensionality reduction, feature selection and a support vector machine classifier to separate the five ovarian carcinoma subtypes using the extracted features. RESULTS: This paper presents the details of our implementation and its validation on a clinically derived dataset of eighty high-resolution histopathology images. The proposed system achieved a multiclass classification accuracy of 95.0% when classifying unseen tissues. Assessment of the classifier's confusion (confusion matrix) between the five different ovarian carcinoma subtypes agrees with clinician's confusion and reflects the difficulty in diagnosing endometrioid and serous carcinomas. CONCLUSIONS: Our results from this first study highlight the difficulty of ovarian carcinoma diagnosis which originate from the intrinsic class-imbalance observed among subtypes and suggest that the automatic analysis of ovarian carcinoma subtypes could be valuable to clinician's diagnostic procedure by providing a second opinion.

Endoscopic scene labelling and augmentation using intraoperative pulsatile motion and colour appearance cues with preoperative anatomical priors.

PURPOSE: Despite great advances in medical image segmentation, the accurate and automatic segmentation of endoscopic scenes remains a challenging problem. Two important aspects have to be considered in segmenting an endoscopic scene: (1) noise and clutter due to light reflection and smoke from cutting tissue, and (2) structure occlusion (e.g. vessels occluded by fat, or endophytic tumours occluded by healthy kidney tissue). METHODS: In this paper, we propose a variational technique to augment a surgeon's endoscopic view by segmenting visible as well as occluded structures in the intraoperative endoscopic view. Our method estimates the 3D pose and deformation of anatomical structures segmented from 3D preoperative data in order to align to and segment corresponding structures in 2D intraoperative endoscopic views. Our preoperative to intraoperative alignment is driven by, first, spatio-temporal, signal processing based vessel pulsation cues and, second, machine learning based analysis of colour and textural visual cues. To our knowledge, this is the first work that utilizes vascular pulsation cues for guiding preoperative to intraoperative registration. In addition, we incorporate a tissue-specific (i.e. heterogeneous) physically based deformation model into our framework to cope with the non-rigid deformation of structures that occurs during the intervention. RESULTS: We validated the utility of our technique on fifteen challenging clinical cases with 45 % improvements in accuracy compared to the state-of-the-art method. CONCLUSIONS: A new technique for localizing both visible and occluded structures in an endoscopic view was proposed and tested. This method leverages both preoperative data, as a source of patient-specific prior knowledge, as well as vasculature pulsation and endoscopic visual cues in order to accurately segment the highly noisy and cluttered environment of an endoscopic video. Our results on in vivo clinical cases of partial nephrectomy illustrate the potential of the proposed framework for augmented reality applications in minimally invasive surgeries.

Misassembly of full-length Disrupted-in-Schizophrenia 1 protein is linked to altered dopamine homeostasis and behavioral deficits.

Disrupted-in-schizophrenia 1 (DISC1) is a mental illness gene first identified in a Scottish pedigree. So far, DISC1-dependent phenotypes in animal models have been confined to expressing mutant DISC1. Here we investigated how pathology of full-length DISC1 protein could be a major mechanism in sporadic mental illness. We demonstrate that a novel transgenic rat model, modestly overexpressing the full-length DISC1 transgene, showed phenotypes consistent with a significant role of DISC1 misassembly in mental illness. The tgDISC1 rat displayed mainly perinuclear DISC1 aggregates in neurons. Furthermore, the tgDISC1 rat showed a robust signature of behavioral phenotypes that includes amphetamine supersensitivity, hyperexploratory behavior and rotarod deficits, all pointing to changes in dopamine (DA) neurotransmission. To understand the etiology of the behavioral deficits, we undertook a series of molecular studies in the dorsal striatum of tgDISC1 rats. We observed an 80% increase in high-affinity DA D2 receptors, an increased translocation of the dopamine transporter to the plasma membrane and a corresponding increase in DA inflow as observed by cyclic voltammetry. A reciprocal relationship between DISC1 protein assembly and DA homeostasis was corroborated by in vitro studies. Elevated cytosolic dopamine caused an increase in DISC1 multimerization, insolubility and complexing with the dopamine transporter, suggesting a physiological mechanism linking DISC1 assembly and dopamine homeostasis. DISC1 protein pathology and its interaction with dopamine homeostasis is a novel cellular mechanism that is relevant for behavioral control and may have a role in mental illness.

Simultaneous Multi-Structure Segmentation and 3D Nonrigid Pose Estimation in Image-Guided Robotic Surgery.

In image-guided robotic surgery, segmenting the endoscopic video stream into meaningful parts provides important contextual information that surgeons can exploit to enhance their perception of the surgical scene. This information provides surgeons with real-time decision-making guidance before initiating critical tasks such as tissue cutting. Segmenting endoscopic video is a challenging problem due to a variety of complications including significant noise attributed to bleeding and smoke from cutting, poor appearance contrast between different tissue types, occluding surgical tools, and limited visibility of the objects' geometries on the projected camera views. In this paper, we propose a multi-modal approach to segmentation where preoperative 3D computed tomography scans and intraoperative stereo-endoscopic video data are jointly analyzed. The idea is to segment multiple poorly visible structures in the stereo/multichannel endoscopic videos by fusing reliable prior knowledge captured from the preoperative 3D scans. More specifically, we estimate and track the pose of the preoperative models in 3D and consider the models' non-rigid deformations to match with corresponding visual cues in multi-channel endoscopic video and segment the objects of interest. Further, contrary to most augmented reality frameworks in endoscopic surgery that assume known camera parameters, an assumption that is often violated during surgery due to non-optimal camera calibration and changes in camera focus/zoom, our method embeds these parameters into the optimization hence correcting the calibration parameters within the segmentation process. We evaluate our technique on synthetic data, ex vivo lamb kidney datasets, and in vivo clinical partial nephrectomy surgery with results demonstrating high accuracy and robustness.

Increased expression of the dopamine transporter leads to loss of dopamine neurons, oxidative stress and l-DOPA reversible motor deficits.

The dopamine transporter is a key protein responsible for regulating dopamine homeostasis. Its function is to transport dopamine from the extracellular space into the presynaptic neuron. Studies have suggested that accumulation of dopamine in the cytosol can trigger oxidative stress and neurotoxicity. Previously, ectopic expression of the dopamine transporter was shown to cause damage in non-dopaminergic neurons due to their inability to handle cytosolic dopamine. However, it is unknown whether increasing dopamine transporter activity will be detrimental to dopamine neurons that are inherently capable of storing and degrading dopamine. To address this issue, we characterized transgenic mice that over-express the dopamine transporter selectively in dopamine neurons. We report that dopamine transporter over-expressing (DAT-tg) mice display spontaneous loss of midbrain dopamine neurons that is accompanied by increases in oxidative stress markers, 5-S-cysteinyl-dopamine and 5-S-cysteinyl-DOPAC. In addition, metabolite-to-dopamine ratios are increased and VMAT2 protein expression is decreased in the striatum of these animals. Furthermore, DAT-tg mice also show fine motor deficits on challenging beam traversal that are reversed with l-DOPA treatment. Collectively, our findings demonstrate that even in neurons that routinely handle dopamine, increased uptake of this neurotransmitter through the dopamine transporter results in oxidative damage, neuronal loss and l-DOPA reversible motor deficits. In addition, DAT over-expressing animals are highly sensitive to MPTP-induced neurotoxicity. The effects of increased dopamine uptake in these transgenic mice could shed light on the unique vulnerability of dopamine neurons in Parkinson's disease.

Efficient multi-organ segmentation in multi-view endoscopic videos using pre-operative priors.

Synergistic fusion of pre-operative (pre-op) and intraoperative (intra-op) imaging data provides surgeons with invaluable insightful information that can improve their decision-making during minimally invasive robotic surgery. In this paper, we propose an efficient technique to segment multiple objects in intra-op multi-view endoscopic videos based on priors captured from pre-op data. Our approach leverages information from 3D pre-op data into the analysis of visual cues in the 2D intra-op data by formulating the problem as one of finding the 3D pose and non-rigid deformations of tissue models driven by features from 2D images. We present a closed-form solution for our formulation and demonstrate how it allows for the inclusion of laparoscopic camera motion model. Our efficient method runs in real-time on a single core CPU making it practical even for robotic surgery systems with limited computational resources. We validate the utility of our technique on ex vivo data as well as in vivo clinical data from laparoscopic partial nephrectomy surgery and demonstrate its robustness in segmenting stereo endoscopic videos.

Local optimization based segmentation of spatially-recurring, multi-region objects with part configuration constraints.

Incorporating prior knowledge into image segmentation algorithms has proven useful for obtaining more accurate and plausible results. Two important constraints, containment and exclusion of regions, have gained attention in recent years mainly due to their descriptive power. In this paper, we augment the level set framework with the ability to handle these two intuitive geometric relationships, containment and exclusion, along with a distance constraint between boundaries of multi-region objects. Level set's important property of automatically handling topological changes of evolving contours/surfaces enables us to segment spatially-recurring objects (e.g., multiple instances of multi-region cells in a large microscopy image) while satisfying the two aforementioned constraints. In addition, the level set approach gives us a very simple and natural way to compute the distance between contours/surfaces and impose constraints on it. The downside, however, is a local optimization framework in which the final segmentation solution depends on the initialization. In fact, here, we sacrifice the optimizability (local instead of global solution) in exchange for lower space complexity (less memory usage) and faster runtime (especially for large microscopic images) as well as no grid artifacts. Nevertheless, the result from validating our method on several biomedical applications showed the utility and advantages of this augmented level set framework (even with rough initialization that is distant from the desired boundaries). We also compared our framework with its counterpart methods in the discrete domain and reported the pros and cons of each of these methods in terms of metrication error and efficiency in memory usage and runtime.

Segmentation of cells with partial occlusion and part configuration constraint using evolutionary computation.

We propose a method for targeted segmentation that identifies and delineates only those spatially-recurring objects that conform to specific geometrical, topological and appearance priors. By adopting a "tribes"-based, global genetic algorithm, we show how we incorporate such priors into a faithful objective function unconcerned about its convexity. We evaluated our framework on a variety of histology and microscopy images to segment potentially overlapping cells with complex topology. Our experiments confirmed the generality, reproducibility and improved accuracy of our approach compared to competing methods.