4.7 Article

A mathematical fuzzy fusion framework for whole tumor segmentation in multimodal MRI using Nakagami imaging

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Brain tumor segmentation using extended Weiner and Laplacian lion optimization algorithm with fuzzy weighted k-mean embedding linear discriminant analysis

Surbhi Vijh et al.

Summary: This paper presents an efficient method for skull stripping to improve decision-making. Extended Weiner filtering is used to remove noise and enhance image quality, and laplacian lion optimization algorithm is implemented to determine the optimal solution. The proposed method outperforms existing algorithms on standard benchmark functions.

NEURAL COMPUTING & APPLICATIONS (2023)

Article Computer Science, Artificial Intelligence

A hybrid weighted fuzzy approach for brain tumor segmentation using MR images

Prabhjot Kaur Chahal et al.

Summary: Detection and classification of human brain tumors are time-consuming yet crucial tasks. This paper proposes a hybrid weighted fuzzy k-means algorithm for brain tumor segmentation using MR images, and successfully identifies tumor types as benign or malignant with the help of SVM. Experimental results show that the proposed method outperforms many existing approaches in terms of accuracy.

NEURAL COMPUTING & APPLICATIONS (2023)

Article Engineering, Electrical & Electronic

Supervoxel-based brain tumor segmentation with multimodal MRI images

Lingling Fang et al.

Summary: MRI has high accuracy and spatial resolution, making it widely used in brain tumor detection. The demand for three-dimensional image segmentation technology is increasing with the development of two-dimensional image segmentation research. This paper proposes a novel 3D supervoxel segmentation method for brain tumors in multimodal MRI images, which demonstrates superior performance compared to other state-of-the-art methods.

SIGNAL IMAGE AND VIDEO PROCESSING (2022)

Article Computer Science, Artificial Intelligence

Low-contrast lesion segmentation in advanced MRI experiments by time-domain Ricker-type wavelets and fuzzy 2-means

Orcan Alpar et al.

Summary: Automated suspicious region segmentation is crucial for experts dealing with contrast-based lesions in MRI images. The study presents an automated framework based on wavelet imaging and fuzzy 2-means for intelligent segmentation of brain lesions. Results show promising performance on clinical and public datasets.

APPLIED INTELLIGENCE (2022)

Article Anatomy & Morphology

Skin cancer detection from dermoscopic images using deep learning and fuzzy k-means clustering

Marriam Nawaz et al.

Summary: This study presents a fully automated method for segmenting melanoma skin cancer using deep learning and fuzzy k-means clustering, aiming to aid in the early diagnosis and treatment of this disease. Evaluation on three standard datasets shows that the method outperforms state-of-the-art approaches in skin lesion recognition and segmentation, demonstrating robustness.

MICROSCOPY RESEARCH AND TECHNIQUE (2022)

Article Computer Science, Information Systems

Fully convolutional neural network with attention gate and fuzzy active contour model for skin lesion segmentation

Thi-Thao Tran et al.

Summary: This study presents a skin lesion segmentation approach based on a fully convolutional neural network and active contour model. The proposed method incorporates skip connection architecture and an attention gate to handle shape and size variations of lesions and improve segmentation accuracy. It also introduces fuzzy energy-based shape distance and applies the active contour model to refine the segmentation. The results show that this approach achieves desired performances compared to other state-of-the-arts on the evaluated databases.

MULTIMEDIA TOOLS AND APPLICATIONS (2022)

Article Computer Science, Artificial Intelligence

Brain tumor segmentation in multimodal MRI images using novel LSIS operator and deep learning

T. Ruba et al.

Summary: This study presents a novel method for tumor segmentation in brain tumor diagnosis using MRI data and deep convolutional neural networks. The proposed method can accurately localize and segment tumors as well as their intra-tumor regions, thus improving the effectiveness of brain tumor treatment planning.

JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING (2022)

Article Computer Science, Artificial Intelligence

Nakagami-Fuzzy imaging framework for precise lesion segmentation in MRI

Orcan Alpar et al.

Summary: The Nakagami distribution and related imaging methods have been proven efficient and promising in medical imaging. A novel NakagamiFuzzy imaging framework is proposed for intelligent and automated segmentation of suspicious regions in brain tumor MRI images, showing high segmentation accuracy.

PATTERN RECOGNITION (2022)

Article Computer Science, Artificial Intelligence

Brain Tumor Segmentation Using Deep Learning and Fuzzy K-Means Clustering for Magnetic Resonance Images

R. Pitchai et al.

Summary: This paper proposes a methodology for brain tumor segmentation using a combination of Artificial Neural Network and Fuzzy K-means algorithm, involving noise removal, attribute extraction and selection, classification, and segmentation stages. The proposed approach achieves high accuracy and sensitivity in segmenting brain tumor regions.

NEURAL PROCESSING LETTERS (2021)

Article Computer Science, Interdisciplinary Applications

Fast level set method for glioma brain tumor segmentation based on Superpixel fuzzy clustering and lattice Boltzmann method

Asieh Khosravanian et al.

Summary: A novel level set method is proposed in this paper for reliable and automatic brain tumor segmentation. Experimental results show that the method is robust to noise, initialization, and intensity non-uniformity, and it is faster and more accurate compared to other state-of-the-art segmentation methods.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2021)

Article Engineering, Electrical & Electronic

ME-Net: Multi-encoder net framework for brain tumor segmentation

Wenbo Zhang et al.

Summary: Our proposed model for brain tumor segmentation with multiple encoders and a new loss function, Categorical Dice, significantly improved performance in segmenting 3D MRI images, effectively addressing voxel imbalance and achieving excellent results in the BraTS 2020 challenge.

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY (2021)

Article Computer Science, Artificial Intelligence

Brain tumor segmentation in MR images using a sparse constrained level set algorithm

Xiaoliang Lei et al.

Summary: This study introduces an automatic sparse constrained level set method for brain tumor segmentation in MR images, achieving high accuracy and stability through the construction of a sparse representation model and an energy function based on the level set method.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

Article Computer Science, Artificial Intelligence

ERV-Net: An efficient 3D residual neural network for brain tumor segmentation

Xinyu Zhou et al.

Summary: This study introduces an efficient 3D residual neural network for brain tumor segmentation, which has less computational complexity and GPU memory consumption. It utilizes a computation-efficient encoder and decoder structure, along with a fusion loss function to improve convergence and tackle data imbalance issues, resulting in excellent experimental results.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

Article Computer Science, Artificial Intelligence

Distribution-based imaging for multiple sclerosis lesion segmentation using specialized fuzzy 2-means powered by Nakagami transmutations

Orcan Alpar et al.

Summary: This study proposes a distribution-based imaging framework enhanced by a specialized fuzzy 2-means algorithm, combined with various distributions to achieve multiple-sclerosis identification and segmentation in FLAIR MRI images. Experimental results indicate that different combinations of distribution parameters have an impact on the final segmentation result.

APPLIED SOFT COMPUTING (2021)

Article Computer Science, Artificial Intelligence

Adaptive melanoma diagnosis using evolving clustering, ensemble and deep neural networks

Teck Yan Tan et al.

KNOWLEDGE-BASED SYSTEMS (2020)

Article Computer Science, Artificial Intelligence

Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation

Tanya Nair et al.

MEDICAL IMAGE ANALYSIS (2020)

Article Computer Science, Artificial Intelligence

Interpretable mammographic mass classification with fuzzy interpolative reasoning

Fangyi Li et al.

KNOWLEDGE-BASED SYSTEMS (2020)

Article Computer Science, Artificial Intelligence

Breast tumor segmentation and shape classification in mammograms using generative adversarial and convolutional neural network

Vivek Kumar Singh et al.

EXPERT SYSTEMS WITH APPLICATIONS (2020)

Article Engineering, Electrical & Electronic

Di-phase midway convolution and deconvolution network for brain tumor segmentation in MRI images

P. L. Chithra et al.

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY (2020)

Article Computer Science, Artificial Intelligence

Brain tumor detection based on extreme learning

Muhammad Sharif et al.

NEURAL COMPUTING & APPLICATIONS (2020)

Article Computer Science, Theory & Methods

An adaptive sparse Bayesian model combined with probabilistic label fusion for multiple sclerosis lesion segmentation in brain MRI

Jingjing Wang et al.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2020)

Article Computer Science, Artificial Intelligence

DeeplGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation

Guotai Wang et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2019)

Article Computer Science, Interdisciplinary Applications

Suspicious-Region Segmentation From Breast Thermogram Using DLPE-Based Level Set Method

Sourav Pramanik et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2019)

Article Computer Science, Artificial Intelligence

Fully automated multi-parametric brain tumour segmentation using superpixel based classification

Zaka Ur Rehman et al.

EXPERT SYSTEMS WITH APPLICATIONS (2019)

Article Computer Science, Artificial Intelligence

A novel fuzzy curvature method for recognition of anterior forearm subcutaneous veins by thermal imaging

Orcan Alpar

EXPERT SYSTEMS WITH APPLICATIONS (2019)

Article Computer Science, Information Systems

Multimodal Medical Image Fusion Based on Fuzzy Discrimination With Structural Patch Decomposition

Yong Yang et al.

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (2019)

Article Health Care Sciences & Services

Efficient Segmentation of Brain Tumor Using FL-SNM with a Metaheuristic Approach to Optimization

Aparna Natarajan et al.

JOURNAL OF MEDICAL SYSTEMS (2019)

Article Computer Science, Interdisciplinary Applications

Ex Vivo and In Vivo Monitoring and Characterization of Thermal Lesions by High-Intensity Focused Ultrasound and Microwave Ablation Using Ultrasonic Nakagami Imaging

Siyuan Zhang et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2018)

Article Computer Science, Artificial Intelligence

Intelligent skin cancer detection using enhanced particle swarm optimization

Teck Yan Tan et al.

KNOWLEDGE-BASED SYSTEMS (2018)

Article Acoustics

HEPATIC STEATOSIS ASSESSMENT WITH ULTRASOUND SMALL-WINDOW ENTROPY IMAGING

Zhuhuang Zhou et al.

ULTRASOUND IN MEDICINE AND BIOLOGY (2018)

Article Engineering, Biomedical

Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI

Mohammadreza Soltaninejad et al.

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY (2017)

Article Computer Science, Artificial Intelligence

MRI segmentation fusion for brain tumor detection

Ivan Cabria et al.

INFORMATION FUSION (2017)

Article Computer Science, Artificial Intelligence

Brain tumor classification from multi-modality MRI using wavelets and machine learning

Khalid Usman et al.

PATTERN ANALYSIS AND APPLICATIONS (2017)

Article Multidisciplinary Sciences

Small-window parametric imaging based on information entropy for ultrasound tissue characterization

Po-Hsiang Tsui et al.

SCIENTIFIC REPORTS (2017)

Article Multidisciplinary Sciences

Evaluation of muscular changes by ultrasound Nakagami imaging in Duchenne muscular dystrophy

Wen-Chin Weng et al.

SCIENTIFIC REPORTS (2017)

Article Multidisciplinary Sciences

Acoustic structure quantification by using ultrasound Nakagami imaging for assessing liver fibrosis

Po-Hsiang Tsui et al.

SCIENTIFIC REPORTS (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)

Article Oncology

Quantitative Ultrasonic Nakagami Imaging of Neck Fibrosis After Head and Neck Radiation Therapy

Xiaofeng Yang et al.

INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS (2015)

Article Engineering, Biomedical

Using Ultrasound Backscattering Signals and Nakagami Statistical Distribution to Assess Regional Cataract Hardness

Miguel Caixinha et al.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2014)

Article Engineering, Biomedical

Nakagami imaging for detecting thermal lesions induced by high-intensity focused ultrasound in tissue

Parisa Rangraz et al.

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE (2014)

Article Acoustics

MODELING OF ERRORS IN NAKAGAMI IMAGING: ILLUSTRATION ON BREAST MASS CHARACTERIZATION

Aymeric Larrue et al.

ULTRASOUND IN MEDICINE AND BIOLOGY (2014)

Article Health Care Sciences & Services

The Virtual Skeleton Database: An Open Access Repository for Biomedical Research and Collaboration

Michael Kistler et al.

JOURNAL OF MEDICAL INTERNET RESEARCH (2013)

Article Engineering, Civil

Nighttime Brake-Light Detection by Nakagami Imaging

Duan-Yu Chen et al.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2012)

Article Computer Science, Information Systems

Salient video cube guided nighttime vehicle braking event detection

Duan-Yu Chen et al.

JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION (2012)

Article Engineering, Biomedical

Three-dimensional ultrasonic Nakagami imaging for tissue characterization

Po-Hsiang Tsui et al.

PHYSICS IN MEDICINE AND BIOLOGY (2010)

Article Acoustics

MICROVASCULAR FLOW ESTIMATION BY MICROBUBBLE-ASSISTED NAKAGAMI IMAGING

Po-Hsiang Tsui et al.

ULTRASOUND IN MEDICINE AND BIOLOGY (2009)

Article Engineering, Biomedical

Classification of breast masses by ultrasonic Nakagami imaging: a feasibility study

Po-Hsiang Tsui et al.

PHYSICS IN MEDICINE AND BIOLOGY (2008)

Article Engineering, Biomedical

Feasibility study of using high-frequency ultrasonic Nakagami imaging for characterizing the cataract lens in vitro

Po-Hsiang Tsui et al.

PHYSICS IN MEDICINE AND BIOLOGY (2007)

Article Acoustics

Imaging local scatterer concentrations by the Nakagami statistical model

Po-Hsiang Tsui et al.

ULTRASOUND IN MEDICINE AND BIOLOGY (2007)

Letter Acoustics

Ultrasonic tissue characterization using a generalized Nakagami model

PM Shankar

IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL (2001)

Article Acoustics

A general statistical model for ultrasonic backscattering from tissues

PM Shankar

IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL (2000)