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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/Smilels/multimodal-translation-teleop

A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU

https://github.com/TsaftarisCollaboratory/CSDisentanglement_Metrics_Library

Disentangled Representation Learning in Cardiac Image Analysis

https://github.com/YannisTzitzikas/GreekMitosStemmer

The Anatomy of Mitos Web Search Engine

https://github.com/adalca/patchlib

Medical Image Imputation from Image Collections

https://github.com/ahmedshahin9/AssistedAnnotator

Extreme Points Derived Confidence Map as a Cue For Class-Agnostic Segmentation Using Deep Neural Network

https://github.com/aitchbi/DIBSI

Domain-Informed Spline Interpolation

https://github.com/ajenningsfrankston/lungmask-master

Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem

https://github.com/alexkaiser/heart_valves

Modeling the Mitral Valve

https://github.com/allenai/dolma

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

https://github.com/anbai106/mlni

Multidimensional representations in late-life depression: convergence in neuroimaging, cognition, clinical symptomatology and genetics

https://github.com/arcadelab/DeepDRR

X-ray-transform Invariant Anatomical Landmark Detection for Pelvic Trauma Surgery

https://github.com/axondeepseg/axondeepseg

Deep Active Learning for Axon-Myelin Segmentation on Histology Data

https://github.com/batmanlab/subject2vec

Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector

https://github.com/bramiozo/PubScience

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

https://github.com/cav-research-lab/predictive-model-delay-correction

Reinforcement Learning with Random Delays

https://github.com/chperkins/Energy_Models

On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models

https://github.com/christianpayer/MedicalDataAugmentationTool-VerSe

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

https://github.com/cswin/AWC

Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis

https://github.com/daxiaHuang/brainstorm

Data augmentation using learned transformations for one-shot medical image segmentation

https://github.com/dbouget/Raidionics-Slicer

AeroPath: An airway segmentation benchmark dataset with challenging pathology

https://github.com/drvelmuruganb/EDD2020-Endoscopy-disease-detection-grand-challenge-2020-

SUMNet: Fully Convolutional Model for Fast Segmentation of Anatomical Structures in Ultrasound Volumes

https://github.com/echonax07/Data_augmentation

Simulating Realistic MRI variations to Improve Deep Learning model and visual explanations using GradCAM

https://github.com/fenghetan9/hyspark

Slide-SAM: Medical SAM Meets Sliding Window

https://github.com/fhaghighi/SemanticGenesis

Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration

https://github.com/fhaghighi/TransVW

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

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

Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs

https://github.com/gaocong13/Projective-Spatial-Transformers

Generalizing Spatial Transformers to Projective Geometry with Applications to 2D/3D Registration

https://github.com/harveerar/smit

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

https://github.com/hilab-git/dag4mia

Contrastive Semi-supervised Learning for Domain Adaptive Segmentation Across Similar Anatomical Structures

https://github.com/jaburke166/octolyzer

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

https://github.com/jeya-maria-jose/Overcomplete-Deep-Subspace-Clustering

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

https://github.com/juliawolleb/anomaly_berdiff

Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI

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

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

https://github.com/lianruizuo/haca3

Optimal operating MR contrast for brain ventricle parcellation

https://github.com/loping151/forplane

E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception

https://github.com/loping151/lerplane

E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception

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