Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies
The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour,
cognition, movement and memory. Although automated segmentation strategies can provide …
cognition, movement and memory. Although automated segmentation strategies can provide …
Transferring Adult-like Phase Images for Robust Multi-view Isointense Infant Brain Segmentation
Accurate tissue segmentation of infant brain in magnetic resonance (MR) images is crucial
for charting early brain development and identifying biomarkers. Due to ongoing myelination …
for charting early brain development and identifying biomarkers. Due to ongoing myelination …
Multi-model medical image segmentation using multi-stage generative adversarial networks
Image segmentation is a challenging problem in medical applications. Medical imaging has
become an integral part of machine learning research, as it enables inspecting interior …
become an integral part of machine learning research, as it enables inspecting interior …
Improving Lung Cancer Diagnosis and Survival Prediction with Deep Learning and CT Imaging
X Wang, J Sharpnack, T Lee - arXiv preprint arXiv:2408.09367, 2024 - arxiv.org
Lung cancer is a major cause of cancer-related deaths, and early diagnosis and treatment
are crucial for improving patients' survival outcomes. In this paper, we propose to employ …
are crucial for improving patients' survival outcomes. In this paper, we propose to employ …
Automatic brain tumor segmentation with domain adaptation
Deep convolution neural networks, in particular, the encoder-decoder networks, have been
extensively used in image segmentation. We develop a deep learning approach for tumor …
extensively used in image segmentation. We develop a deep learning approach for tumor …
Double-branch U-Net for multi-scale organ segmentation
U-Net has achieved great success in the task of medical image segmentation. It encodes
and extracts information from several convolution blocks, and then decodes the feature …
and extracts information from several convolution blocks, and then decodes the feature …
A survey of MRI-based brain tissue segmentation using deep learning
L Wu, S Wang, J Liu, L Hou, N Li, F Su, X Yang… - Complex & Intelligent …, 2025 - Springer
Segmentation of brain tissue from MR images provides detailed quantitative brain analysis
for accurate diagnosis, detection, and classification of brain diseases, and plays an …
for accurate diagnosis, detection, and classification of brain diseases, and plays an …
A Review of Recent Advancements in Infant Brain MRI Segmentation Using Deep Learning Approaches
In this paper, a critical analysis of recent trends and techniques for tissue segmentation of an
pediatric brain Magnetic Resonance Imaging (MRI) is performed. A significant amount of …
pediatric brain Magnetic Resonance Imaging (MRI) is performed. A significant amount of …
Segmentation of brain tissues from infant mri records using machine learning techniques
B Surányi, L Kovács, L Szilágyi - 2021 IEEE 19th World …, 2021 - ieeexplore.ieee.org
The automatic segmentation of medical images is an intensely investigated problem, due to
the quick rise of medical image data amount created day by day, which cannot be followed …
the quick rise of medical image data amount created day by day, which cannot be followed …
[HTML][HTML] 基于深度学习的脑图像分割算法研究综述
玉丽王， 子健赵 - Sheng Wu Yi Xue Gong Cheng Xue Za Zhi …, 2020 - ncbi.nlm.nih.gov
基于深度学习的脑图像分割算法是目前的一个研究热点。 本文首先对脑图像分割的意义以及
相关算法内容进行系统阐述， 突出了基于深度学习的脑图像分割算法的优势。 然后 …
相关算法内容进行系统阐述， 突出了基于深度学习的脑图像分割算法的优势。 然后 …