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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/evihuijben/ood_detection_mri

공식 코드

Enhancing Reconstruction-Based Out-of-Distribution Detection in Brain MRI with Model and Metric Ensembles

https://github.com/faresbougourzi/d-trattunet

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D-TrAttUnet: Toward Hybrid CNN-Transformer Architecture for Generic and Subtle Segmentation in Medical Images

https://github.com/faustomilletari/VNet

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

https://github.com/faysal-md/an-interpretable-deep-learning-approach-for-skin-cancer-categorization-ieee2023

공식 코드

An Interpretable Deep Learning Approach for Skin Cancer Categorization

https://github.com/fbernardpi/sparsePdmFitting

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Shape-aware Surface Reconstruction from Sparse 3D Point-Clouds

https://github.com/fbladl/nvum

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NVUM: Non-Volatile Unbiased Memory for Robust Medical Image Classification

https://github.com/fei-hdu/NAS-Lung

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Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules Classification

https://github.com/fengbeiliu/semi-chest

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Self-supervised Mean Teacher for Semi-supervised Chest X-ray Classification

https://github.com/few-shot-learning-on-chest-x-ray/fsl_subspace

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Few-shot Diagnosis of Chest x-rays Using an Ensemble of Random Discriminative Subspaces

https://github.com/finnbehrendt/ensembled-ssim-for-unsupervised-anomaly-detection

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Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly Detection

https://github.com/fjssharpsword/ATH

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Deep Triplet Hashing Network for Case-based Medical Image Retrieval

https://github.com/flux661/Capsule-Vision-2024-Solution-Team_Layer_Players

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

https://github.com/fmlinks/domain

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Unsupervised Domain Adaptation for Brain Vessel Segmentation through Transwarp Contrastive Learning

https://github.com/frankkramer-lab/covid19.MIScnn

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Automated Chest CT Image Segmentation of COVID-19 Lung Infection based on 3D U-Net

https://github.com/function2-llx/pumit

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Building Universal Foundation Models for Medical Image Analysis with Spatially Adaptive Networks

https://github.com/gaodengfan/msmorph

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MsMorph: An Unsupervised pyramid learning network for brain image registration

https://github.com/gaozhitong/SP_guided_Noisy_Label_Seg

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Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation

https://github.com/geoaigroup/geoai-ecrs2023

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Trainable Noise Model as an XAI evaluation method: application on Sobol for remote sensing image segmentation

https://github.com/gianlucarloni/crocodile

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CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning

https://github.com/gigantenbein/UNet-Zoo

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RevPHiSeg: A Memory-Efficient Neural Network for Uncertainty Quantification in Medical Image Segmentation

https://github.com/global-health-labs/us-dcgan

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How Good Are Synthetic Medical Images? An Empirical Study with Lung Ultrasound

https://github.com/goodaycoder/jdac

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Iterative Learning for Joint Image Denoising and Motion Artifact Correction of 3D Brain MRI

https://github.com/guanghuifu/medical_dino_eval

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Comparative Analysis of ImageNet Pre-Trained Deep Learning Models and DINOv2 in Medical Imaging Classification

https://github.com/guo-stone/mambamorph

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MambaMorph: a Mamba-based Framework for Medical MR-CT Deformable Registration

https://github.com/gvalvano/sdtnet

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Temporal Consistency Objectives Regularize the Learning of Disentangled Representations

https://github.com/gvtulder/cross-view-transformers

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Multi-view analysis of unregistered medical images using cross-view transformers

https://github.com/haail/glog-csunet

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GLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image Segmentation

https://github.com/hananshafi/medcontext

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MedContext: Learning Contextual Cues for Efficient Volumetric Medical Segmentation

https://github.com/hanhpt23/silvarmed

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SilVar-Med: A Speech-Driven Visual Language Model for Explainable Abnormality Detection in Medical Imaging

https://github.com/haonenglin/awesome-vlm-for-mia

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Taming Vision-Language Models for Medical Image Analysis: A Comprehensive Review

https://github.com/haoxu0507/ipmi25-sam-assisted-registration

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Medical Image Registration Meets Vision Foundation Model: Prototype Learning and Contour Awareness

https://github.com/haoxuanli-thu/dbf-unet

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DBF-UNet: A Two-Stage Framework for Carotid Artery Segmentation with Pseudo-Label Generation

https://github.com/harryanthony/evaluating_ood_detection

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Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection

https://github.com/hasibzunair/uniformizing-3D

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Uniformizing Techniques to Process CT scans with 3D CNNs for Tuberculosis Prediction

https://github.com/hazardfy/fiba

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FIBA: Frequency-Injection based Backdoor Attack in Medical Image Analysis

https://github.com/healthx-lab/medclip-samv2

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MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image Segmentation

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