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Segmentation

Papers

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Showing 6076–6100 of 13072 papers

TitleStatusHype
Automatic segmentation of prostate zones—0
Deep Learning Segmentation and Classification of Red Blood Cells Using a Large Multi-Scanner Dataset—0
Deep Learning Pipeline for Preprocessing and Segmenting Cardiac Magnetic Resonance of Single Ventricle Patients from an Image Registry—0
Automatic segmentation of Organs at Risk in Head and Neck cancer patients from CT and MRI scans—0
A Model for Image Segmentation in Retina—0
Active Learning Enabled Low-cost Cell Image Segmentation Using Bounding Box Annotation—0
Deep Learning Pipeline for Fully Automated Myocardial Infarct Segmentation from Clinical Cardiac MR Scans—0
Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation—0
Deep Learning Models Delineates Multiple Nuclear Phenotypes in H&E Stained Histology Sections—0
Deep Learning Methods for Retinal Blood Vessel Segmentation: Evaluation on Images with Retinopathy of Prematurity—0
Novel coronavirus pneumonia lesion segmentation in CT images—0
Amodal segmentation just like doing a jigsaw—0
Deep Learning Methods for Lung Cancer Segmentation in Whole-slide Histopathology Images -- the ACDC@LungHP Challenge 2019—0
Deep Learning Markov Random Field for Semantic Segmentation—0
Automatic Segmentation of Muscle Tissue and Inter-muscular Fat in Thigh and Calf MRI Images—0
Deep Learning in Multi-organ Segmentation—0
Automatic segmentation of MR brain images with a convolutional neural network—0
Active Label Refinement for Semantic Segmentation of Satellite Images—0
3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training—0
2D Amodal Instance Segmentation Guided by 3D Shape Prior—0
Deep Learning in Medical Ultrasound Image Segmentation: a Review—0
Automatic segmentation of meniscus based on MAE self-supervision and point-line weak supervision paradigm—0
Deep Learning from Dual-Energy Information for Whole-Heart Segmentation in Dual-Energy and Single-Energy Non-Contrast-Enhanced Cardiac CT—0
Deep Learning Framework with Multi-Head Dilated Encoders for Enhanced Segmentation of Cervical Cancer on Multiparametric Magnetic Resonance Imaging—0
Amodal Panoptic Segmentation—0
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All datasetsSA-1B.MFSDMMFloodSimGas

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1unSAM+ (Semi-supervised)Average Precision42.8—Unverified
2SAMAverage Precision38.9—Unverified
#ModelMetricClaimedVerifiedStatus
1HNN10%20—Unverified
#ModelMetricClaimedVerifiedStatus
1ABANetF1 Score96.82—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50 + DeepLabV3+F1 score0.77—Unverified
#ModelMetricClaimedVerifiedStatus
1LangGasIoU0.69—Unverified