4.6 Article

MTDCNet: A 3D multi-threading dilated convolutional network for brain tumor automatic segmentation

Related references

Note: Only part of the references are listed.
Article Radiology, Nuclear Medicine & Medical Imaging

Automated post-operative brain tumour segmentation: A deep learning model based on transfer learning from pre-operative images

Mina Ghaffari et al.

Summary: This study developed an automated method for brain tumour segmentation using multimodal brain scans and manual annotations, achieving high accuracy through ensemble learning and data transfer techniques even with a small dataset.

MAGNETIC RESONANCE IMAGING (2022)

Article Computer Science, Artificial Intelligence

Cross-modality deep feature learning for brain tumor segmentation

Dingwen Zhang et al.

Summary: This study proposes a novel cross-modality deep feature learning framework for brain tumor segmentation from multi-modality MRI data. By incorporating cross-modality feature transition and fusion processes, the framework is able to effectively improve the performance of brain tumor segmentation.

PATTERN RECOGNITION (2021)

Article Computer Science, Artificial Intelligence

Segmentation of the multimodal brain tumor image used the multi-pathway architecture method based on 3D FCN

Jindong Sun et al.

Summary: The study proposed a novel model based on deep learning for accurate segmentation of multimodal brain tissues from 3D medical images. The model achieved effective segmentation on two brain tumor segmentation datasets, demonstrating its potential as a powerful tool for studying medical images of brain tumors.

NEUROCOMPUTING (2021)

Article Computer Science, Artificial Intelligence

MSMANet: A multi-scale mesh aggregation network for brain tumor segmentation

Yan Zhang et al.

Summary: The fine segmentation of brain tumor is crucial for diagnosis, treatment planning, and prognosis, and has become a research hotspot. Automated segmentation methods based on convolutional neural networks have gained significant attention. A novel multi-scale mesh aggregation network (MSMANet) is proposed for brain tumor segmentation, achieving improved feature extraction, aggregation, and convergence through innovative strategies. Experimental results demonstrate satisfactory performance compared to state-of-the-art methods.

APPLIED SOFT COMPUTING (2021)

Article Computer Science, Artificial Intelligence

Brain tumor segmentation with deep convolutional symmetric neural network

Hao Chen et al.

NEUROCOMPUTING (2020)

Article Computer Science, Interdisciplinary Applications

DENSE-INception U -net for medical image segmentation

Ziang Zhang et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Brain SegNet: 3D local refinement network for brain lesion segmentation

Xiaojun Hu et al.

BMC MEDICAL IMAGING (2020)

Article Engineering, Biomedical

DeepSeg: deep neural network framework for automatic brain tumor segmentation using magnetic resonance FLAIR images

Ramy A. Zeineldin et al.

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY (2020)

Article Computer Science, Artificial Intelligence

Segmentation of breast ultrasound image with semantic classification of superpixels

Qinghua Huang et al.

MEDICAL IMAGE ANALYSIS (2020)

Article Engineering, Biomedical

Brain tumor segmentation using 3D Mask R-CNN for dynamic susceptibility contrast enhanced perfusion imaging

Jiwoong Jeong et al.

PHYSICS IN MEDICINE AND BIOLOGY (2020)

Article Computer Science, Artificial Intelligence

A Unified Framework for Generalizable Style Transfer: Style and Content Separation

Yexun Zhang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

An Intensity Variation Pattern Analysis Based Machine Learning Classifier for MRI Brain Tumor Detection

Muthalakshmi Murugesan et al.

CURRENT MEDICAL IMAGING (2019)

Article Health Care Sciences & Services

DRRNet: Dense Residual Refine Networks for Automatic Brain Tumor Segmentation

Jiawei Sun et al.

JOURNAL OF MEDICAL SYSTEMS (2019)

Article Imaging Science & Photographic Technology

A fully automatic methodology for MRI brain tumour detection and segmentation

S. Tchoketch Kebir et al.

IMAGING SCIENCE JOURNAL (2019)

Article Computer Science, Artificial Intelligence

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

Liang-Chieh Chen et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2018)

Article Neurosciences

Behavioral interventions for reducing head motion during MRI scans in children

Deanna J. Greene et al.

NEUROIMAGE (2018)

Article Computer Science, Information Systems

Kernel sparse representation for MRI image analysis in automatic brain tumor segmentation

Ji-jun Tong et al.

FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING (2018)

Article Multidisciplinary Sciences

A Novel M-ACA-Based Tumor Segmentation and DAPP Feature Extraction with PPCSO-PKC-Based MRI Classification

Adhi Lakshmi et al.

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING (2018)

Article Computer Science, Artificial Intelligence

Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation

Konstantinos Kamnitsas et al.

MEDICAL IMAGE ANALYSIS (2017)

Article Computer Science, Artificial Intelligence

Brain tumor segmentation with Deep Neural Networks

Mohammad Havaei et al.

MEDICAL IMAGE ANALYSIS (2017)

Article Radiology, Nuclear Medicine & Medical Imaging

Brain tumor segmentation using holistically nested neural networks in MRI images

Ying Zhuge et al.

MEDICAL PHYSICS (2017)

Review Neurosciences

Glial Cells and Their Function in the Adult Brain: A Journey through the History of Their Ablation

Sarah Jakel et al.

FRONTIERS IN CELLULAR NEUROSCIENCE (2017)

Article Computer Science, Hardware & Architecture

ImageNet Classification with Deep Convolutional Neural Networks

Alex Krizhevsky et al.

COMMUNICATIONS OF THE ACM (2017)

Article Computer Science, Interdisciplinary Applications

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images

Sergio Pereira et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)

Article Radiology, Nuclear Medicine & Medical Imaging

Reference-based MRI

Lior Weizman et al.

MEDICAL PHYSICS (2016)

Article Computer Science, Interdisciplinary Applications

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

Bjoern H. Menze et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2015)

Review Computer Science, Artificial Intelligence

Review of brain MRI image segmentation methods

M. A. Balafar et al.

ARTIFICIAL INTELLIGENCE REVIEW (2010)

Article Computer Science, Information Systems

MRI fuzzy segmentation of brain tissue using neighborhood attraction with neural-network optimization

S Shen et al.

IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE (2005)