4.5 Review

Review of Deep Learning Approaches for the Segmentation of Multiple Sclerosis Lesions on Brain MRI

Related references

Note: Only part of the references are listed.
Review Computer Science, Interdisciplinary Applications

State-of-the-Art Segmentation Techniques and Future Directions for Multiple Sclerosis Brain Lesions

Amrita Kaur et al.

Summary: This paper provides a systematic review of automated multiple sclerosis lesion segmentation in the literature, analyzing the complexity of lesions and classification of existing automatic methods. It also presents a comparative analysis of various MS segmentation techniques, identifying future directions for further research in this field.

ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING (2021)

Article Clinical Neurology

Deep learning segmentation of gadolinium-enhancing lesions in multiple sclerosis

Ivan Coronado et al.

Summary: This study evaluates the performance of deep learning CNNs in segmenting gadolinium-enhancing lesions in a large cohort of MS patients. The best segmentation performance was achieved when the input included all five multispectral image sets, especially for enhancement volume > 70 mm(3).

MULTIPLE SCLEROSIS JOURNAL (2021)

Article Automation & Control Systems

Weighted LIC-Based Structure Tensor With Application to Image Content Perception and Processing

Yuhui Zheng et al.

Summary: In this article, a novel ANLST construction method is proposed by combining tensor decomposition with weighted line integral convolution, aiming at deeply exploring and exploiting the spatial direction relevancy of the tensors for their regularization. The experimental results demonstrate that the proposed method outperforms current representative nonlinear structure tensors, and it can be applied in industrial surveillance systems to enhance image perception and quality.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)

Review Engineering, Electrical & Electronic

Review of advanced computational approaches on multiple sclerosis segmentation and classification

Manimurugan Shanmuganathan et al.

IET SIGNAL PROCESSING (2020)

Article Mathematical & Computational Biology

Unsupervised Domain Adaptation With Optimal Transport in Multi-Site Segmentation of Multiple Sclerosis Lesions From MRI Data

Antoine Ackaouy et al.

FRONTIERS IN COMPUTATIONAL NEUROSCIENCE (2020)

Article Computer Science, Interdisciplinary Applications

Neuro-fuzzy patch-wise R-CNN for multiple sclerosis segmentation

Ehab Essa et al.

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING (2020)

Article Engineering, Biomedical

Multiple sclerosis lesion activity segmentation with attention-guided two-path CNNs

Nils Gessert et al.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2020)

Proceedings Paper Engineering, Biomedical

SCANNER INVARIANT MULTIPLE SCLEROSIS LESION SEGMENTATION FROM MRI

Shahab Aslani et al.

2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020) (2020)

Article Computer Science, Artificial Intelligence

Automatic spondylolisthesis grading from MRIs across modalities using faster adversarial recognition network

Shen Zhao et al.

MEDICAL IMAGE ANALYSIS (2019)

Article Computer Science, Information Systems

Robust Segmentation of Intima-Media Borders With Different Morphologies and Dynamics During the Cardiac Cycle

Shen Zhao et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2018)

Article Radiology, Nuclear Medicine & Medical Imaging

A level set method for multiple sclerosis lesion segmentation

Yue Zhao et al.

MAGNETIC RESONANCE IMAGING (2018)

Article Computer Science, Hardware & Architecture

An efficient multiple sclerosis segmentation and detection system using neural networks

Mohammad H. Alshayeji et al.

COMPUTERS & ELECTRICAL ENGINEERING (2018)

Article Computer Science, Artificial Intelligence

Direct delineation of myocardial infarction without contrast agents using a joint motion feature learning architecture

Chenchu Xu et al.

MEDICAL IMAGE ANALYSIS (2018)

Review Engineering, Biomedical

Survey of automated multiple sclerosis lesion segmentation techniques on magnetic resonance imaging

Antonios Danelakis et al.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2018)

Article Radiology, Nuclear Medicine & Medical Imaging

DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning

Ke Yan et al.

JOURNAL OF MEDICAL IMAGING (2018)

Proceedings Paper Computer Science, Theory & Methods

Ensemble of Multi-sized FCNs to Improve White Matter Lesion Segmentation

Zhewei Wang et al.

MACHINE LEARNING IN MEDICAL IMAGING: 9TH INTERNATIONAL WORKSHOP, MLMI 2018 (2018)

Article Computer Science, Artificial Intelligence

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Vijay Badrinarayanan et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)

Article Computer Science, Interdisciplinary Applications

Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation

Tom Brosch et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)

Article Computer Science, Interdisciplinary Applications

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

Hoo-Chang Shin et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)

Proceedings Paper Computer Science, Information Systems

Longitudinal Multiple Sclerosis Lesion Segmentation Using Multi-view Convolutional Neural Networks

Ariel Birenbaum et al.

DEEP LEARNING AND DATA LABELING FOR MEDICAL APPLICATIONS (2016)

Review Computer Science, Artificial Intelligence

Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging

Daniel Garcia-Lorenzo et al.

MEDICAL IMAGE ANALYSIS (2013)

Article Computer Science, Information Systems

Segmentation of multiple sclerosis lesions in brain MRI: A review of automated approaches

Xavier Llado et al.

INFORMATION SCIENCES (2012)

Article Clinical Neurology

Segmentation of multiple sclerosis lesions in MR images: a review

Daryoush Mortazavi et al.

NEURORADIOLOGY (2012)

Article Clinical Neurology

Diagnostic Criteria for Multiple Sclerosis: 2010 Revisions to the McDonald Criteria

Chris H. Polman et al.

ANNALS OF NEUROLOGY (2011)

Article Computer Science, Artificial Intelligence

Domain Adaptation via Transfer Component Analysis

Sinno Jialin Pan et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS (2011)

Article Engineering, Biomedical

A framework for evaluating image segmentation algorithms

JK Udupa et al.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2006)