Papers with Code 아카이브
Brain Image Segmentation
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Deep Learning-Based Brain Image Segmentation for Automated Tumour Detection
Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging
One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma
Finding the Most Transferable Tasks for Brain Image Segmentation
ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data
Learning from imperfect training data using a robust loss function: application to brain image segmentation
Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images
An Open-Source Tool for Longitudinal Whole-Brain and White Matter Lesion Segmentation
DAM-AL: Dilated Attention Mechanism with Attention Loss for 3D Infant Brain Image Segmentation
Automatic quality control framework for more reliable integration of machine learning-based image segmentation into medical workflows
Multi-Task Neural Processes
EGMM: an Evidential Version of the Gaussian Mixture Model for Clustering
A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis
A Contrast-Adaptive Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis
Using deep convolutional neural networks for neonatal brain image segmentation
ROAM: Random Layer Mixup for Semi-Supervised Learning in Medical Imaging
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
Transfer Learning from Partial Annotations for Whole Brain Segmentation
Enforcing temporal consistency in Deep Learning segmentation of brain MR images
Unsupervised Deep Learning for Bayesian Brain MRI Segmentation
Data augmentation using learned transformations for one-shot medical image segmentation
Non-local U-Net for Biomedical Image Segmentation
Brain Segmentation from k-space with End-to-end Recurrent Attention Network
The Method of Multimodal MRI Brain Image Segmentation Based on Differential Geometric Features
Automatic Brain Structures Segmentation Using Deep Residual Dilated U-Net
Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines
Towards integrating spatial localization in convolutional neural networks for brain image segmentation
Large Scale Image Segmentation with Structured Loss based Deep Learning for Connectome Reconstruction
Combination of Hidden Markov Random Field and Conjugate Gradient for Brain Image Segmentation
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics
Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.