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Anatomy

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

https://github.com/guoyu-niubility/dsd-3d-unsupervised-landmark-detection-based-motion-estimation

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Unsupervised Landmark Detection Based Spatiotemporal Motion Estimation for 4D Dynamic Medical Images

https://github.com/gvalvano/sdtnet

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Temporal Consistency Objectives Regularize the Learning of Disentangled Representations

https://github.com/gzoumpourlis/ensemble-mi

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Motor Imagery Decoding Using Ensemble Curriculum Learning and Collaborative Training

https://github.com/hao1635/ascon

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ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT Denoising

https://github.com/hasan1292/mddpm

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Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model

https://github.com/hieuphan33/miccai2024-unest

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Structural Attention: Rethinking Transformer for Unpaired Medical Image Synthesis

https://github.com/hitachinsk/tha

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A Dataset for Deep Learning-based Bone Structure Analyses in Total Hip Arthroplasty

https://github.com/hreynaud/dartagnan

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D'ARTAGNAN: Counterfactual Video Generation

https://github.com/hrlblab/asign

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ASIGN: An Anatomy-aware Spatial Imputation Graphic Network for 3D Spatial Transcriptomics

https://github.com/hrlblab/hats

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HATs: Hierarchical Adaptive Taxonomy Segmentation for Panoramic Pathology Image Analysis

https://github.com/hsiangyuzhao/adler

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AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation

https://github.com/hugorichard/multiviewica

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Modeling Shared Responses in Neuroimaging Studies through MultiView ICA

https://github.com/i-vesseg/multivesseg

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Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA

https://github.com/iamlab-ryerson/flowreg

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FlowReg: Fast Deformable Unsupervised Medical Image Registration using Optical Flow

https://github.com/icans-strasbourg/psat

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PSAT: Pediatric Segmentation Approaches via Adult Augmentations and Transfer Learning

https://github.com/icon-lab/pGAN-cGAN

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Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networks

https://github.com/iducvlab/cov19d

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Deep Learning Based Automated COVID-19 Classification from Computed Tomography Images

https://github.com/imagingdatacommons/cloudsegmentatorresults

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Rule-based outlier detection of AI-generated anatomy segmentations

https://github.com/imfusiongmbh/disa-universal-multimodal-registration

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DISA: DIfferentiable Similarity Approximation for Universal Multimodal Registration

https://github.com/iyerkrithika21/Mesh2SSMJournal

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Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes

https://github.com/iyerkrithika21/mesh2ssm_2023

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Mesh2SSM: From Surface Meshes to Statistical Shape Models of Anatomy

https://github.com/jaburke166/sloctolyzer

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SLOctolyzer: Fully automatic analysis toolkit for segmentation and feature extracting in scanning laser ophthalmoscopy images

https://github.com/jadie1/bvib-deepssm

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Fully Bayesian VIB-DeepSSM

https://github.com/jadie1/point2ssm

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Point2SSM: Learning Morphological Variations of Anatomies from Point Cloud

https://github.com/jbdel/vilmedic

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Toward expanding the scope of radiology report summarization to multiple anatomies and modalities

https://github.com/jemtan/fpi

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Detecting Outliers with Foreign Patch Interpolation

https://github.com/jeya-maria-jose/KiU-Net-pytorch

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KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations

https://github.com/jianbojiao/awcl

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Anatomy-Aware Contrastive Representation Learning for Fetal Ultrasound

https://github.com/jianningli/medshapenet-feedback

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MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

https://github.com/jiaqiw01/MRIAnatEval

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Evaluating the Quality of Brain MRI Generators

https://github.com/jlianglab/caid

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CAiD: Context-Aware Instance Discrimination for Self-supervised Learning in Medical Imaging

https://github.com/jlianglab/eden

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Towards Foundation Models Learned from Anatomy in Medical Imaging via Self-Supervision

https://github.com/jlianglab/peac

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Learning Anatomically Consistent Embedding for Chest Radiography

https://github.com/jongdory/damt

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Domain Aware Multi-Task Pretraining of 3D Swin Transformer for T1-weighted Brain MRI

https://github.com/joshuaomolegan/tta-for-3d-fetal-subcortical-segmentation

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Exploring Test Time Adaptation for Subcortical Segmentation of the Fetal Brain in 3D Ultrasound

https://github.com/jun-sato/anatpaste

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Anatomy-aware Self-supervised Learning for Anomaly Detection in Chest Radiographs

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