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Lesion Segmentation

Lesion segmentation is the task of segmenting out lesions from other objects in medical based images.

( Image credit: D-UNet )

Papers

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Showing 576–600 of 640 papers

TitleStatusHype
Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networksCode0
The Effects of Image Pre- and Post-Processing, Wavelet Decomposition, and Local Binary Patterns on U-Nets for Skin Lesion Segmentation—0
Uncertainty quantification using Bayesian neural networks in classification: Application to ischemic stroke lesion segmentation—0
Segmentation of Multiple Sclerosis lesion in brain MR images using Fuzzy C-Means—0
Asymmetric Loss Functions and Deep Densely Connected Networks for Highly Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection—0
Multiple Sclerosis Lesion Segmentation from Brain MRI via Fully Convolutional Neural Networks—0
Towards Clinical Diagnosis: Automated Stroke Lesion Segmentation on Multimodal MR Image Using Convolutional Neural Network—0
Comparative Analysis of Unsupervised Algorithms for Breast MRI Lesion Segmentation—0
Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image SegmentationCode0
Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network—0
Encoder-Decoder with Atrous Separable Convolution for Semantic Image SegmentationCode1
Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST—0
Dense Pooling layers in Fully Convolutional Network for Skin Lesion SegmentationCode0
Semi-Automatic Algorithm for Breast MRI Lesion Segmentation Using Marker-Controlled Watershed Transformation—0
Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review—0
Detection-aided liver lesion segmentation using deep learningCode0
Road Extraction by Deep Residual U-NetCode1
Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)Code1
DeepLesion: Automated Deep Mining, Categorization and Detection of Significant Radiology Image Findings using Large-Scale Clinical Lesion AnnotationsCode1
Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks—0
Skin Lesion Segmentation: U-Nets versus Clustering—0
H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT VolumesCode0
Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation—0
Liver lesion segmentation informed by joint liver segmentation—0
Tversky loss function for image segmentation using 3D fully convolutional deep networksCode0
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