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An improved 3D-UNet-based brain hippocampus segmentation model based on MR images
ObjectiveAccurate delineation of the hippocampal region via magnetic resonance imaging (MRI) is crucial for the prevention and early diagnosis of...
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Segmentation of macular neovascularization and leakage in fluorescein angiography images in neovascular age-related macular degeneration using deep learning
Background/objectivesWe aim to develop an objective fully automated Artificial intelligence (AI) algorithm for MNV lesion size and leakage area...
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Automated segmentation and volume prediction in pediatric Wilms’ tumor CT using nnu-net
BackgroundRadiologic volumetric evaluation of Wilms’ tumor (WT) is an important indicator to guide treatment decisions. However, due to the...
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Development of a volumetric pancreas segmentation CT dataset for AI applications through trained technologists: a study during the COVID 19 containment phase
PurposeTo evaluate the performance of trained technologists vis-à-vis radiologists for volumetric pancreas segmentation and to assess the impact of...
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Vessel filtering and segmentation of coronary CT angiographic images
PurposeCoronary artery segmentation in coronary computed tomography angiography (CTA) images plays a crucial role in diagnosing cardiovascular...
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From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery
PurposePreventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has...
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Structured light for touchless 3D registration in video-based surgical navigation
PurposeArthroscopic surgery, with its inherent difficulties on visibility and maneuverability inside the joint, poses significant challenges to...
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Retrospective in silico evaluation of optimized preoperative planning for temporal bone surgery
PurposeRobot-assisted surgery at the temporal bone utilizing a flexible drilling unit would allow safer access to clinical targets such as the...
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Sources of performance variability in deep learning-based polyp detection
PurposeValidation metrics are a key prerequisite for the reliable tracking of scientific progress and for deciding on the potential clinical...
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Automatic Cardiac Structure Contouring for Small Datasets with Cascaded Deep Learning Models
Cardiac structure contouring is a time consuming and tedious manual activity used for radiotherapeutic dose toxicity planning. We developed an...
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Self-supervised learning via cluster distance prediction for operating room context awareness
PurposeSemantic segmentation and activity classification are key components to create intelligent surgical systems able to understand and assist...
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Automated segmentation of liver segment on portal venous phase MR images using a 3D convolutional neural network
ObjectiveWe aim to develop and validate a three-dimensional convolutional neural network (3D-CNN) model for automatic liver segment segmentation on...
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Improving the Quantitative Analysis of Breast Microcalcifications: A Multiscale Approach
Accurate characterization of microcalcifications (MCs) in 2D digital mammography is a necessary step toward reducing the diagnostic uncertainty...
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On the usage of average Hausdorff distance for segmentation performance assessment: hidden error when used for ranking
Average Hausdorff distance is a widely used performance measure to calculate the distance between two point sets. In medical image segmentation, it...
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Aberrant patterns of PET response during treatment for DLBCL patients with MYC gene rearrangements
PurposeMYC gene rearrangements in diffuse large B-cell lymphoma (DLBCL) patients are associated with poor prognosis. Our aim was to compare patterns...
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Aortic wall segmentation in 18F-sodium fluoride PET/CT scans: Head-to-head comparison of artificial intelligence-based versus manual segmentation
BackgroundWe aimed to establish and test an automated AI-based method for rapid segmentation of the aortic wall in positron emission...
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Effect of MRI acquisition acceleration via compressed sensing and parallel imaging on brain volumetry
ObjectivesTo investigate the effect of compressed SENSE (CS), an acceleration technique combining parallel imaging and compressed sensing, on...
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Deep Learning in Radiation Oncology Treatment Planning for Prostate Cancer: A Systematic Review
Radiation oncology for prostate cancer is important as it can decrease the morbidity and mortality associated with this disease. Planning for this...
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Boundary Restored Network for Subpleural Pulmonary Lesion Segmentation on Ultrasound Images at Local and Global Scales
To evaluate the application of machine learning for the detection of subpleural pulmonary lesions (SPLs) in ultrasound (US) scans, we propose a novel...
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Toward an automatic preoperative pipeline for image-guided temporal bone surgery
PurposeMinimally invasive surgery is often built upon a time-consuming preoperative step consisting of segmentation and trajectory planning. At the...
