Lesion Segmentation
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Benchmarks
ISIC 2018
BUS 2017 Dataset B
PH2
HAM10000
ISIC 2017
ISIC 2018 Task 1
ISLES-2015
Most implemented
U-Net: Convolutional Networks for Biomedical Image Segmentation
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Pyramid Scene Parsing Network
Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)
Road Extraction by Deep Residual U-Net
Papers
Synthetic training for long-tail haemorrhagic lesion segmentation in data-scarce settings
Cerebral microbleeds (CMBs) and cortical superficial siderosis (cSS) are imaging markers of cerebral small vessel disease, but their automated segmentation is limited by the scarcity of positive cases and voxel-level ann…
Lesion SegmentationLightMedSeg-ISLES: Stroke Lesion Segmentation with 81x Fewer Parameters than nnU-Net
Large networks and ensembles often lead medical image segmentation challenges, but their storage and inference demands complicate deployment. We present LightMedSeg-ISLES, a 1.26-million-parameter pipeline for T1-weighte…
Medical Image SegmentationLesion SegmentationCGSM: Concept-Guided Segmentation Model for Precise Pulmonary Lesion Delineation
Accurate segmentation of pulmonary lesions is essential for effective clinical diagnosis and treatment strategies. Existing segmentation approaches often lack task-specific semantic guidance, as text-based annotations ty…
Lesion SegmentationAnatomy-Aware Promptable Segmentation with Online Interactive Training for AUTOPET V
We present an anatomy-aware, promptable model for whole-body lesion segmentation in FDG and PSMA PET/CT, developed for the AUTOPET V challenge. The proposed method is built as family of nnU-Net-based models and trained i…
Lesion SegmentationLess Contouring, More Accuracy: Lesion-Guided ROI Deep Learning for Ovarian Ultrasound Classification
Ovarian lesion classification using transvaginal ultrasound remains challenging due to overlapping imaging characteristics and the dependence on expert interpretation. This study investigates whether lesion-guided region…
Binary ClassificationLesion SegmentationDeep Learning Segmentation of Diffusion-Weighted MRI Acute Ischaemic Stroke: A Pragmatic Evaluation Across Three Datasets
Objective: Diffusion-weighted MRI (DWI-MRI) is the gold standard for visualizing and quantifying acute ischaemic stroke (AIS). Although deep learning methods can accurately segment AIS lesions, the optimal image inputs a…
Lesion Segmentation