Probabilistic hierarchical clustering based identification and segmentation of brain tumors in magnetic resonance imaging
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Title
Probabilistic hierarchical clustering based identification and segmentation of brain tumors in magnetic resonance imaging
Authors
Keywords
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Journal
Biomedical Engineering-Biomedizinische Technik
Volume -, Issue -, Pages -
Publisher
Walter de Gruyter GmbH
Online
2023-10-24
DOI
10.1515/bmt-2021-0313
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Related references
Note: Only part of the references are listed.- Brain Tumor Segmentation Using Deep Learning and Fuzzy K-Means Clustering for Magnetic Resonance Images
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- An improved Gabor wavelet transform and rough K-means clustering algorithm for MRI brain tumor image segmentation
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- Effective segmentation and classification of brain tumor using rough K means algorithm and multi kernel SVM in MR images
- (2020) S. Krishnakumar et al. Journal of Ambient Intelligence and Humanized Computing
- A Clinical Support System for Brain Tumor Classification Using Soft Computing Techniques
- (2019) P. Rupa Ezhil Arasi et al. JOURNAL OF MEDICAL SYSTEMS
- A review on brain tumor segmentation of MRI images
- (2019) Anjali Wadhwa et al. MAGNETIC RESONANCE IMAGING
- Brain Tumor Segmentation and Classification from Magnetic Resonance Images: Review of selected methods from 2014 to 2019
- (2019) Arti Tiwari et al. PATTERN RECOGNITION LETTERS
- Machine learning based brain tumour segmentation on limited data using local texture and abnormality
- (2018) Stijn Bonte et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Brain tumor segmentation using DE embedded OTSU method and neural network
- (2018) Anshika Sharma et al. MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING
- A K-Means-Galactic Swarm Optimization-Based Clustering Algorithm with Otsu’s Entropy for Brain Tumor Detection
- (2018) Satyasai Jagannath Nanda et al. APPLIED ARTIFICIAL INTELLIGENCE
- K-Means clustering and neural network for object detecting and identifying abnormality of brain tumor
- (2018) N. Arunkumar et al. SOFT COMPUTING
- Detection of Brain Tumor based on Features Fusion and Machine Learning
- (2018) Javeria Amin et al. Journal of Ambient Intelligence and Humanized Computing
- Automated brain tumour segmentation techniques- A review
- (2017) M. Angulakshmi et al. INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY
- Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
- (2017) Konstantinos Kamnitsas et al. MEDICAL IMAGE ANALYSIS
- A Novel Brain Tumor Segmentation from Multi-Modality MRI via A Level-Set-Based Model
- (2016) Yantao Song et al. Journal of Signal Processing Systems for Signal Image and Video Technology
- Using a Method Based on a Modified K-Means Clustering and Mean Shift Segmentation to Reduce File Sizes and Detect Brain Tumors from Magnetic Resonance (MRI) Images
- (2016) JiHoon Kim et al. WIRELESS PERSONAL COMMUNICATIONS
- The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
- (2015) Bjoern H. Menze et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
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