Papers with Code 아카이브

Skull Stripping

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

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코드

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

https://github.com/BBillot/SynthSR

공식 코드

Joint super-resolution and synthesis of 1 mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast

https://github.com/KurtLabUW/ISLES2024

공식 코드

How We Won the ISLES'24 Challenge by Preprocessing

https://github.com/TIO-IKIM/PhaseGen

공식 코드

PhaseGen: A Diffusion-Based Approach for Complex-Valued MRI Data Generation

https://github.com/TIO-IKIM/k-Strip

공식 코드

k-strip: A novel segmentation algorithm in k-space for the application of skull stripping

https://github.com/brainlesion/preprocessing

공식 코드

BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis

https://github.com/christiantinauer/binADNI

공식 코드

Pfungst and Clever Hans: Identifying the unintended cues in a widely used Alzheimer's disease MRI dataset using explainable deep learning

https://github.com/gama-ufsc/brain-extraction-for-tumor-segmentation

공식 코드

Towards fully automated deep-learning-based brain tumor segmentation: is brain extraction still necessary?

https://github.com/jmlipman/MedicDeepLabv3Plus

공식 코드

Automatic cerebral hemisphere segmentation in rat MRI with lesions via attention-based convolutional neural networks

https://github.com/luca2245/disarmpp_harmonization

공식 코드

DISARM++: Beyond scanner-free harmonization

https://github.com/medimair/brain-mri-processing-pipeline

공식 코드

Negligible effect of brain MRI data preprocessing for tumor segmentation

https://github.com/novestars/neural-pre-processing

공식 코드

Neural Pre-Processing: A Learning Framework for End-to-end Brain MRI Pre-processing

https://github.com/pjsjongsung/PUMBA

공식 코드

Skull stripping with purely synthetic data

https://github.com/raun1/Complementary_Segmentation_Network

공식 코드

CompNet: Complementary Segmentation Network for Brain MRI Extraction

https://github.com/rauschecker-sugrue-labs/kspace-segmentation

공식 코드

Domain Influence in MRI Medical Image Segmentation: spatial versus k-space inputs

https://github.com/shruti-jadon/Semantic-Segmentation-Loss-Functions

공식 코드

A survey of loss functions for semantic segmentation

https://github.com/ymli39/ACEnet-for-Neuroanatomy-Segmentation

공식 코드

ACEnet: Anatomical Context-Encoding Network for Neuroanatomy Segmentation

https://github.com/MICLab-Unicamp/CONSNet

Convolutional Neural Networks for Skull-stripping in Brain MR Imaging using Consensus-based Silver standard Masks

https://github.com/SenthilCaesar/CNN-Brain-MRI-Segmentation

CompNet: Complementary Segmentation Network for Brain MRI Extraction

https://github.com/TornikeAm/Semantic-Segmentation-on-Pascal-VOC

A survey of loss functions for semantic segmentation

https://github.com/ehosseiniasl/3d-convolutional-network

Alzheimer's Disease Diagnostics by Adaptation of 3D Convolutional Network

https://github.com/mahima672000/Brain-MRI-Segmentation

Training of a Skull-Stripping Neural Network with efficient data augmentation

https://github.com/pnlbwh/CNN-Diffusion-MRIBrain-Segmentation

CompNet: Complementary Segmentation Network for Brain MRI Extraction

https://github.com/raun1/Complementary_Segmentation_Network-Raw-Code-Available-Under-Construction-

CompNet: Complementary Segmentation Network for Brain MRI Extraction

https://github.com/raun1/ISBI-2020-LITS_Hybrid_Comp_Net

CompNet: Complementary Segmentation Network for Brain MRI Extraction

https://github.com/raun1/LITS_Hybrid_Comp_Net

CompNet: Complementary Segmentation Network for Brain MRI Extraction

https://github.com/raun1/MICCAI2018---Complementary_Segmentation_Network-Raw-Code

CompNet: Complementary Segmentation Network for Brain MRI Extraction

https://github.com/raun1/MICCAI2018---Complementary_Segmentation_Network-Raw-Code-Available-Under-Construction-

CompNet: Complementary Segmentation Network for Brain MRI Extraction

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