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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/Puckett-Lab/explainability_CorticalSurfaceGDL

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An explainability framework for cortical surface-based deep learning

https://github.com/STNLd2/FBPAug

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Zero-Shot Domain Adaptation in CT Segmentation by Filtered Back Projection Augmentation

https://github.com/Shef-AIRE/MeDSLIP

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MeDSLIP: Medical Dual-Stream Language-Image Pre-training for Fine-grained Alignment

https://github.com/SiyuLiu0329/python-3d-image-augmentation

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Generalisable 3D Fabric Architecture for Streamlined Universal Multi-Dataset Medical Image Segmentation

https://github.com/SophieDvali/FunconnNetworkAnalysis

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Diverging network architecture of the $\textit{C. elegans}$ connectome and signaling network

https://github.com/StefanDenn3r/Unsupervised_Anomaly_Detection_Brain_MRI

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Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study

https://github.com/Stochastik-TU-Ilmenau/image-template-resolution

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Quantifying the Resolution of a Template after Image Registration

https://github.com/UK-Digital-Heart-Project/lvae_mlp

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Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

https://github.com/ZerojumpLine/DecGAN

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Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition

https://github.com/Zi-YuanYang/SCAN-PhysFed

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Patient-Level Anatomy Meets Scanning-Level Physics: Personalized Federated Low-Dose CT Denoising Empowered by Large Language Model

https://github.com/abcyzj/Semantics2Hands

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Semantics2Hands: Transferring Hand Motion Semantics between Avatars

https://github.com/abenhamadou/3dteethseg22_challenge

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3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge

https://github.com/adalca/papago

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Medical Image Imputation from Image Collections

https://github.com/adalca/voxelorb

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Predictive Modeling of Anatomy with Genetic and Clinical Data

https://github.com/agis85/anatomy_modality_decomposition

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Disentangled Representation Learning in Cardiac Image Analysis

https://github.com/agis85/multimodal_segmentation

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Disentangle, align and fuse for multimodal and semi-supervised image segmentation

https://github.com/ai-med/halos

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HALOS: Hallucination-free Organ Segmentation after Organ Resection Surgery

https://github.com/alessandro-f/dif-fuse

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Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images

https://github.com/alexaatm/UnsupervisedSegmentor4Ultrasound

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Deep Spectral Methods for Unsupervised Ultrasound Image Interpretation

https://github.com/alexanderbaumann99/s3m

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S3M: Scalable Statistical Shape Modeling through Unsupervised Correspondences

https://github.com/alexanderjaus/apex

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Anatomy-guided Pathology Segmentation

https://github.com/alexanderjaus/atlasdataset

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Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelines

https://github.com/alexisthual/fugw

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Aligning individual brains with Fused Unbalanced Gromov-Wasserstein

https://github.com/alexkaiser/mitral_valve

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Modeling the Mitral Valve

https://github.com/alibaba-damo-academy/fvlm

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Large-scale and Fine-grained Vision-language Pre-training for Enhanced CT Image Understanding

https://github.com/alibaba-damo-academy/med_query

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Med-Query: Steerable Parsing of 9-DoF Medical Anatomies with Query Embedding

https://github.com/alibaba-damo-academy/self-supervised-anatomical-embedding-v2

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SAM: Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Images

https://github.com/alkanc/autosamp

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AutoSamp: Autoencoding k-space Sampling via Variational Information Maximization for 3D MRI

https://github.com/alkanc/tfnufft

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AutoSamp: Autoencoding k-space Sampling via Variational Information Maximization for 3D MRI

https://github.com/amigolab/synthanatomy

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Morphology-preserving Autoregressive 3D Generative Modelling of the Brain

https://github.com/amita-giri/fratio-based-method-for-source-enumeration

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An F-ratio-Based Method for Estimating the Number of Active Sources in MEG

https://github.com/an-michaelg/rt4u

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Reliable Multi-View Learning with Conformal Prediction for Aortic Stenosis Classification in Echocardiography

https://github.com/anjany/verse

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VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images

https://github.com/anthony-mendil/modiffae

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Motion Diffusion Autoencoders: Enabling Attribute Manipulation in Human Motion Demonstrated on Karate Techniques

https://github.com/apelykh/hand-to-diffusion

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Giving a Hand to Diffusion Models: a Two-Stage Approach to Improving Conditional Human Image Generation

https://github.com/arseniionuchin/worm_clusterization

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Perspectives and constraints on neural network models of neurobiological processes

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