Papers with Code 아카이브

MRI segmentation

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

https://github.55860.com/perceivelab/panknet

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Hierarchical 3D Feature Learning for Pancreas Segmentation

https://github.com/920232796/nestedformer

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NestedFormer: Nested Modality-Aware Transformer for Brain Tumor Segmentation

https://github.com/AIGeeksGroup/MediAug

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MediAug: Exploring Visual Augmentation in Medical Imaging

https://github.com/BBillot/SynthSeg

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A Learning Strategy for Contrast-agnostic MRI Segmentation

https://github.com/HiLab-git/WSL4MIS

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Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision

https://github.com/Holmes696/Probabilistic-Hadamard-U-Net

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A Probabilistic Hadamard U-Net for MRI Bias Field Correction

https://github.com/LucasFidon/HardnessWeightedSampler

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Distributionally Robust Deep Learning using Hardness Weighted Sampling

https://github.com/LucasFidon/fetal-brain-segmentation-partial-supervision-miccai21

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Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation

https://github.com/LucasFidon/label-set-loss-functions

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Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation

https://github.com/MIPT-Oulu/RobustCartilageSegmentation

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Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain Adaptation

https://github.com/NIC-VICOROB/SUNet-architecture

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Acute and sub-acute stroke lesion segmentation from multimodal MRI

https://github.com/NIC-VICOROB/stroke-mri-segmentation

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Acute and sub-acute stroke lesion segmentation from multimodal MRI

https://github.com/Powertony102/corn_official

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Leveraging CORAL-Correlation Consistency Network for Semi-Supervised Left Atrium MRI Segmentation

https://github.com/ad12/DOSMA

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The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

https://github.com/adalca/neuron

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Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation

https://github.com/anthonyweidai/SvANet

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Exploiting Scale-Variant Attention for Segmenting Small Medical Objects

https://github.com/aywi/mprotonet

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MProtoNet: A Case-Based Interpretable Model for Brain Tumor Classification with 3D Multi-parametric Magnetic Resonance Imaging

https://github.com/bangwayne/verse

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VerSe: Integrating Multiple Queries as Prompts for Versatile Cardiac MRI Segmentation

https://github.com/c-feng/DirectionalFeature

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Learning Directional Feature Maps for Cardiac MRI Segmentation

https://github.com/cgalaz01/mnms2_challenge

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Tempera: Spatial Transformer Feature Pyramid Network for Cardiac MRI Segmentation

https://github.com/cheng-01037/causality-medical-image-domain-generalization

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Causality-inspired Single-source Domain Generalization for Medical Image Segmentation

https://github.com/cheng-01037/probability_calibration_for_ood_mri_segmentation

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Improved post-hoc probability calibration for out-of-domain MRI segmentation

https://github.com/christophreich1996/oss-net

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OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data

https://github.com/cuttle-fish-my/gm-guided-dg

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Gradient-Map-Guided Adaptive Domain Generalization for Cross Modality MRI Segmentation

https://github.com/deep-mi/neonatevinna

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VINNA for Neonates -- Orientation Independence through Latent Augmentations

https://github.com/deeptag/cstm

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Continuous Spatio-Temporal Memory Networks for 4D Cardiac Cine MRI Segmentation

https://github.com/devavrattomar/sst

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Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation

https://github.com/duyhominhnguyen/LVM-Med

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LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching

https://github.com/farzad-bz/harmonizing-flows

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Harmonizing Flows: Unsupervised MR harmonization based on normalizing flows

https://github.com/haail/fins-for-biomedical-imaging

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Feature Imitating Networks Enhance The Performance, Reliability And Speed Of Deep Learning On Biomedical Image Processing Tasks

https://github.com/haoningwu3639/MRGen

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MRGen: Diffusion-based Controllable Data Engine for MRI Segmentation towards Unannotated Modalities

https://github.com/harveerar/PSIGAN

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PSIGAN: Joint probabilistic segmentation and image distribution matching for unpaired cross-modality adaptation based MRI segmentation

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

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An Uncertainty-guided Tiered Self-training Framework for Active Source-free Domain Adaptation in Prostate Segmentation

https://github.com/hilab-git/upl-sfda

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UPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation

https://github.com/josedolz/LiviaNET

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Isointense Infant Brain Segmentation with a Hyper-dense Connected Convolutional Neural Network

https://github.com/josedolz/SemiDenseNet

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Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation

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