Papers with Code 아카이브

Medical Image Analysis

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/farrell236/SVRnet

Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry

https://github.com/fhaghighi/SemanticGenesis

Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning

https://github.com/fhaghighi/TransVW

Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning

https://github.com/fitushar/AI-in-Lung-Health-Benchmarking-Detection-and-Diagnostic-Models-Across-Multiple-CT-Scan-Datasets

Med3D: Transfer Learning for 3D Medical Image Analysis

https://github.com/forderation/breast-cancer-retrieval

https://github.com/frankkramer-lab/MIScnn/blob/master/miscnn/neural_network/metrics.py

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation

https://github.com/funnyzhou/C2L_MICCAI2020

Comparing to Learn: Surpassing ImageNet Pretraining on Radiographs By Comparing Image Representations

https://github.com/gift-surg/fetal_brain_seg

NiftyNet: a deep-learning platform for medical imaging

https://github.com/harveerar/smit

Self-supervised 3D anatomy segmentation using self-distilled masked image transformer (SMIT)

https://github.com/himanshunaidu/cnn_adnan_fruit

Medical Image Retrieval using Deep Convolutional Neural Network

https://github.com/hungyiwu/mixed-distance

Barcode Annotations for Medical Image Retrieval: A Preliminary Investigation

https://github.com/ibrahimayaz/Fila-GAN

Synthesizing Filamentary Structured Images with GANs

https://github.com/ivanwilliammd/I3DR-Net-Transfer-Learning

Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection

https://github.com/iversonicter/Learn-to-pay-attention

Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

https://github.com/jackyko1991/vnet-tensorflow

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

https://github.com/jacobzhaoziyuan/DSAL

Deeply Supervised Active Learning for Finger Bones Segmentation

https://github.com/jgrieb/object-detection-service

Detection and Annotation of Plant Organs from Digitized Herbarium Scans using Deep Learning

https://github.com/jgrieb/plant-detection-service

Detection and Annotation of Plant Organs from Digitized Herbarium Scans using Deep Learning

https://github.com/julianbertini/MSNet

NiftyNet: a deep-learning platform for medical imaging

https://github.com/jusiro/fewshot-finetuning

Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis

https://github.com/jw4hv/geo-sic

VoxelMorph: A Learning Framework for Deformable Medical Image Registration

https://github.com/kacel33/fixed-DeepSEED

DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder Convolutional Neural Networks for Pulmonary Nodule Detection

https://github.com/kingo233/FCT-Pytorch

The Fully Convolutional Transformer for Medical Image Segmentation

https://github.com/lajipeng/Recursive-Cascaded-Networks-master

VoxelMorph: A Learning Framework for Deformable Medical Image Registration

https://github.com/learningtitans/data-depth-design

Knowledge Transfer for Melanoma Screening with Deep Learning

https://github.com/learningtitans/isbi2017-part3

Knowledge Transfer for Melanoma Screening with Deep Learning

https://github.com/levayz/protosam

DINOv2 based Self Supervised Learning For Few Shot Medical Image Segmentation

https://github.com/liangbright/OOD_Attack_NN

Adversarial Robustness Study of Convolutional Neural Network for Lumbar Disk Shape Reconstruction from MR images

https://github.com/liupeng0606/voting

Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis

https://github.com/liuquande/SRC-MT

Semi-supervised Medical Image Classification with Relation-driven Self-ensembling Model

https://github.com/lsqshr/AH-Net

3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes

https://github.com/lukasuz/Banding-Pattern-Extraction

Deep Anomaly Generation: An Image Translation Approach of Synthesizing Abnormal Banded Chromosome Images

https://github.com/machiraju-lab/ua-cnn

Self supervised contrastive learning for digital histopathology

https://github.com/mattmacy/vnet.pytorch

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

https://github.com/medical-image-analysis-laboratory/fetmrqc

FetMRQC: Automated Quality Control for fetal brain MRI

https://github.com/mida-project/prototype-multi-modality-assistant

BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.