ArticleMedical & biological engineering & computing2017
A computerized volumetric segmentation method applicable to multi-centre MRI data to support computer-aided breast tissue analysis, density assessment and lesion localization.
Article in Medical & biological engineering & computing, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Automated Segmentation of Tissues Using CT and MRI: A Systematic Review.Academic radiology · 2019Pooled it
- Pooled it
- Domain Shift in Breast DCE-MRI Tumor Segmentation: A Balanced LoCoCV Study on the MAMA-MIA Dataset.Diagnostics (Basel, Switzerland) · 2026Article
- Improving signal-to-noise ratio by maximal convolution of longitudinal and transverse magnetization components in MRI: application to the breast cancer detection.Medical & biological engineering & computing · 2024Article
- Current and Emerging Magnetic Resonance-Based Techniques for Breast Cancer.Frontiers in medicine · 2020Review
- Recent Progress for the Techniques of MRI-Guided Breast Interventions and their applications on Surgical Strategy.Journal of Cancer · 2020Review
- Automatic Breast and Fibroglandular Tissue Segmentation in Breast MRI Using Deep Learning by a Fully-Convolutional Residual Neural Network U-Net.Academic radiology · 2019Article
- Quantitative Measurements of Breast Density Using Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2019Review
- Automated breast tumor detection and segmentation with a novel computational framework of whole ultrasound images.Medical & biological engineering & computing · 2018Review
- Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis.Computational and mathematical methods in medicine · 2018Review
- Automatic outer and inner breast tissue segmentation using multi-parametric MRI images of breast tumor patients.PloS one · 2018Article
- Breast MRI segmentation for density estimation: Do different methods give the same results and how much do differences matter?Medical physics · 2017Article
- Automated modification and fusion of voxel models to construct body phantoms with heterogeneous breast tissue: Application to MRI simulations.Journal of biomedical graphics and computing · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Density assessment and lesion localization in breast MRI require accurate segmentation of breast tissues. A fast, computerized algorithm for volumetric breast segmentation, suitable for multi-centre data, has been developed, employing 3D bias-corrected fuzzy c-means clustering and morphological operations. The full breast extent is determined on T1-weighted images without prior information concerning breast anatomy. Left and right breasts are identified separately using automatic detection of the midsternum. Statistical analysis of breast volumes from eighty-two women scanned in a UK multi-centre study of MRI screening shows that the segmentation algorithm performs well when compared with manually corrected segmentation, with high relative overlap (RO), high true-positive volume fraction (TPVF) and low false-positive volume fraction (FPVF), and has an overall performance of RO 0.94 ± 0.05, TPVF 0.97 ± 0.03 and FPVF 0.04 ± 0.06, respectively (training: 0.93 ± 0.05, 0.97 ± 0.03 and 0.04 ± 0.06; test: 0.94 ± 0.05, 0.98 ± 0.02 and 0.05 ± 0.07).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.