Papers with Code 아카이브
Medical Image Segmentation
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Medical Image Segmentation is a computer vision task that involves dividing an medical image into multiple segments, where each segment represents a different object or structure of interest in the image. The goal of medical image segmentation is to provide a precise and accurate representation of the objects of interest within the image, typically for the purpose of diagnosis, treatment planning, and quantitative analysis.
<span style="color:grey; opacity: 0.6">( Image credit: IVD-Net )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Rakeshvd/Semantic-Segmenation-of-MRI-scan-using-Mask-RCNN
https://github.com/RameshBattu/Convolutional-Neural-Network-on-CIFAR-10-DataSet
https://github.com/RegulusReggie/CS259
Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks
https://github.com/Rintarooo/PSPNet
https://github.com/RituYadav92/Image-segmentation
https://github.com/RituYadav92/Radar-RGB-Attentive-Multimodal-Object-Detection
https://github.com/RobinRajSB/Brain-Tumor-Segmentation-Using-CNN
https://github.com/Robinatp/Deeplab_Tensorflow
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
https://github.com/RoichatulJannah21/neural-odes-segmentation
Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands
https://github.com/Rosie-Brigham/sesmeg
https://github.com/Rust401/pixel2piexl
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/SANCHES-Pedro/Segmentation_3D_DeepLearning
Cerebrovascular Network Segmentation on MRA Images with Deep Learning
https://github.com/SANKHA1/Vehicle-Detection
https://github.com/SINGROUP/ED-AFM
https://github.com/SK124/Semantic-Segmentaion-Using-UNets
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/SLDGroup/CASCADE
https://github.com/SSN15/Behavioral-Cloning--Implementaion-of-Autonomous-car-using-deep-learning
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/STASYA00/UrbanGen
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/SUYEgit/Surgery-Robot-Detection-Segmentation
https://github.com/SWKoreaBME/D-Unet_PyTorch
D-UNet: a dimension-fusion U shape network for chronic stroke lesion segmentation
https://github.com/SWKoreaBME/sangwook_kits2019
Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge
https://github.com/SahinTiryaki/Brain-tumor-segmentation-Vgg19UNet
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/Sakib1263/DenseNet-1D-2D-Tensorflow-Keras
https://github.com/SarthakGarg13/Severstal-Steel-Defect-Detection
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/Sempronius/LITS_test
Detection-aided liver lesion segmentation using deep learning
https://github.com/SenthilCaesar/CNN-Brain-MRI-Segmentation
QuickNAT: A Fully Convolutional Network for Quick and Accurate Segmentation of Neuroanatomy
https://github.com/SeonbeomKim/TensorFlow-pix2pix
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/SfTI-Robotics/ROS-label-node
https://github.com/ShahedSabab/imagePrep
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/ShaileshKumar97/Speech-Enhancement
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/SharadGitHub/OctaveUnet
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/Sharut/CT_Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/ShawFromAttock/FYP-Medical-Image-Segmentation-using-Nested-UNet-Architecture
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
https://github.com/ShimaRafiei-IUT/DFCN
Dense Pooling layers in Fully Convolutional Network for Skin Lesion Segmentation
https://github.com/ShiyuLiang/odin-pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.