https://github.com/lyqcom/2D-unet
U-Net: Convolutional Networks for Biomedical Image Segmentation
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/lyqcom/3d-unet
3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation
https://github.com/lyqcom/PMCNet
Progressive Multi-scale Consistent Network for Multi-class Fundus Lesion Segmentation
https://github.com/lyqcom/convlstm
Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions
https://github.com/mad2001/cardiac_ucla
A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI
https://github.com/mandalarotation/PixdosepiX-OpenKBP---2020-AAPM-Grand-Challenge-
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/manideep2510/eye-in-the-sky
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/manideep2510/melanoma_segmentation
Automatic skin lesion segmentation with fully convolutional-deconvolutional networks
https://github.com/manigalati/quality_control_CMR
Efficient Model Monitoring for Quality Control in Cardiac Image Segmentation
https://github.com/manuelhz/dissertation
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
https://github.com/marc-gorriz/CEAL-Medical-Image-Segmentation
https://github.com/marccoru/marinedebrisdetector
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
https://github.com/marcdcfischer/punetr
Prompt Tuning for Parameter-efficient Medical Image Segmentation
https://github.com/mariosfourn/ScienceBowl
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/marload/ConvNets-TensorFlow2
https://github.com/marrlab/dispr
https://github.com/massucattoj/unet-model
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/mastanimahdi/pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/matanrein/Understanding-Clouds-from-Satellite-Images
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/mateuszbuda/brain-segmentation-pytorch
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/mathildor/DeepLab-v3
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
https://github.com/matlab-deep-learning/pix2pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/mattangus/fast-semantic-segmentation
https://github.com/matteo-bastico/coupledlaplacian
https://github.com/mattmacy/vnet.pytorch
V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
https://github.com/maxfrei750/DeepParticleNet
https://github.com/maxfrei750/FibeR-CNN
https://github.com/mazurowski-lab/SlicerSegmentHumanBody
SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRI
https://github.com/mberkay0/pretrained-backbones-unet
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/mcaseyrehm/pix2pixColab
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/mdt48/semantic-segmentation-pytorch
https://github.com/medical-image-analysis-laboratory/fetalsynthseg
Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain Imaging
https://github.com/medicinetoken/medical-graph-rag
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
https://github.com/medicl-vu/prism
Interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound images
https://github.com/mediteamC/teamC
VoxResNet: Deep Voxelwise Residual Networks for Volumetric Brain Segmentation
https://github.com/mehrdad-noori/brain-tumor-segmentation
Attention-Guided Version of 2D UNet for Automatic Brain Tumor Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.