Convolutional neural network in medical image analysis: a review

SS Kshatri, D Singh - Archives of Computational Methods in Engineering, 2023 - Springer
Medical image analysis helps in resolving clinical issues by examining clinically generated
images. In today's world of deep learning (DL) along with advances in computer vision, the …

A review on brain structures segmentation in magnetic resonance imaging

S González-Villà, A Oliver, S Valverde, L Wang… - Artificial intelligence in …, 2016 - Elsevier
Background and objectives Automatic brain structures segmentation in magnetic resonance
images has been widely investigated in recent years with the goal of hel** diagnosis and …

Unsupervised domain adaptation of MRI skull-strip** trained on adult data to newborns

A Omidi, A Mohammadshahi… - Proceedings of the …, 2024 - openaccess.thecvf.com
Skull-strip** is an important first step when analyzing brain Magnetic Resonance Imaging
(MRI) data. Deep learning-based supervised segmentation models, such as the U-net …

3D brain tumor segmentation in MRI using fuzzy classification, symmetry analysis and spatially constrained deformable models

H Khotanlou, O Colliot, J Atif, I Bloch - Fuzzy sets and systems, 2009 - Elsevier
We propose a new general method for segmenting brain tumors in 3D magnetic resonance
images. Our method is applicable to different types of tumors. First, the brain is segmented …

Comparative evaluation of registration algorithms in different brain databases with varying difficulty: results and insights

Y Ou, H Akbari, M Bilello, X Da… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
Evaluating various algorithms for the inter-subject registration of brain magnetic resonance
images (MRI) is a necessary topic receiving growing attention. Existing studies evaluated …

Fuzzy spatial relation ontology for image interpretation

C Hudelot, J Atif, I Bloch - Fuzzy Sets and Systems, 2008 - Elsevier
The semantic interpretation of images can benefit from representations of useful concepts
and the links between them as ontologies. In this paper, we propose an ontology of spatial …