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Medical Image Analysis

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코드

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

https://github.com/hic-messaoudi/cross-dimensional-transfer-learning-in-medical-image-segmentation-with-deep-learning

공식 코드

Cross-dimensional transfer learning in medical image segmentation with deep learning

https://github.com/hilab-git/dca-net

공식 코드

Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation

https://github.com/honkamj/sitreg

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SITReg: Multi-resolution architecture for symmetric, inverse consistent, and topology preserving image registration

https://github.com/horsepurve/StyleSegor

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Neural Style Transfer Improves 3D Cardiovascular MR Image Segmentation on Inconsistent Data

https://github.com/hritam-98/MFSNet

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MFSNet: A Multi Focus Segmentation Network for Skin Lesion Segmentation

https://github.com/hrlblab/SimTriplet

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SimTriplet: Simple Triplet Representation Learning with a Single GPU

https://github.com/huanglizi/stpnet

공식 코드

STPNet: Scale-aware Text Prompt Network for Medical Image Segmentation

https://github.com/hust-linyi/cat-net

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Few Shot Medical Image Segmentation with Cross Attention Transformer

https://github.com/huyhieupham/learning-from-multiple-annotators

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Learning from Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis

https://github.com/hyn2028/llm-cxr

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LLM-CXR: Instruction-Finetuned LLM for CXR Image Understanding and Generation

https://github.com/i-am-tobi/Capsule_Vision_Challenge_2024

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Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy

https://github.com/iWeisskohl/Evidential-neural-network-for-lymphoma-segmentation

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Evidential segmentation of 3D PET/CT images

https://github.com/iman2693/gdsm

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Brain Age Estimation with a Greedy Dual-Stream Model for Limited Datasets

https://github.com/imesluh/vocalfolds

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A Dataset of Laryngeal Endoscopic Images with Comparative Study on Convolution Neural Network Based Semantic Segmentation

https://github.com/imogenqi/SMA

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Stabilized Medical Image Attacks

https://github.com/imsy-dkfz/prevalence-shifts

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Deployment of Image Analysis Algorithms under Prevalence Shifts

https://github.com/ipmi-icns-uke/sparsam

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Self-supervision for medical image classification: state-of-the-art performance with ~100 labeled training samples per class

https://github.com/ispamm/QWT

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Generalizing Medical Image Representations via Quaternion Wavelet Networks

https://github.com/ituvisionlab/Uncertainty-Based-Dynamic-Graph-Neighborhoods

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Uncertainty-Based Dynamic Graph Neighborhoods For Medical Segmentation

https://github.com/ividja/Probabilistic-PII

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Confidence-Aware and Self-Supervised Image Anomaly Localisation

https://github.com/iyerkrithika21/morph_ler

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MORPH-LER: Log-Euclidean Regularization for Population-Aware Image Registration

https://github.com/jacob-thrasher/te-ssl

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TE-SSL: Time and Event-aware Self Supervised Learning for Alzheimer's Disease Progression Analysis

https://github.com/jadie1/medseguq

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Benchmarking Scalable Epistemic Uncertainty Quantification in Organ Segmentation

https://github.com/jamesqfreeman/miceye

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Follow My Eye: Using Gaze to Supervise Computer-Aided Diagnosis

https://github.com/jcreinhold/intensity-normalization

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Evaluating the Impact of Intensity Normalization on MR Image Synthesis

https://github.com/jerry-boss/drvd-bench

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DrVD-Bench: Do Vision-Language Models Reason Like Human Doctors in Medical Image Diagnosis?

https://github.com/jianningli/voxel_rearrangement

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Learning to Rearrange Voxels in Binary Segmentation Masks for Smooth Manifold Triangulation

https://github.com/jianzhang96/goodsad

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PKU-GoodsAD: A Supermarket Goods Dataset for Unsupervised Anomaly Detection and Segmentation

https://github.com/jiarunliu/swin-umamba

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Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining

https://github.com/jiasongchen/SPIE-2021

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

https://github.com/jiayichen815/feal

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Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts

https://github.com/jink-ucla/OpenManus-SimpleMind

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Autonomous Computer Vision Development with Agentic AI

https://github.com/jlianglab/benchmarktransferlearning

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A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis

https://github.com/jlianglab/dira

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DiRA: Discriminative, Restorative, and Adversarial Learning for Self-supervised Medical Image Analysis

https://github.com/jlianglab/peac

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Learning Anatomically Consistent Embedding for Chest Radiography

https://github.com/jongdory/aldm

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Adaptive Latent Diffusion Model for 3D Medical Image to Image Translation: Multi-modal Magnetic Resonance Imaging Study

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