Automated Single and Multi-Breast Tumor Segmentation Using Improved Watershed Technique in 2D MRI Images

Author:

Taheri Mohammad1,Hamer George1,Son Seong Ho2,Shin Sung Y.1

Affiliation:

1. Department of Electrical Engineering and Computer Science, South Dakota State University, Brookings, SD, USA

2. Radio Technology Research Department Electronics and Telecommunications Research Institute (ETRI), Daejeon, South Korea

Publisher

ACM

Reference17 articles.

1. "Cancer Statistics Center." {Online}. Available: https://cancerstatisticscenter.cancer.org/?_ga=1.242628866.1838802877.1464045043#/. "Cancer Statistics Center." {Online}. Available: https://cancerstatisticscenter.cancer.org/?_ga=1.242628866.1838802877.1464045043#/.

2. Automatic image segmentation of nuclear stained breast tissue sections using color active contour model and an improved watershed method

3. Segmentation and Characterization of Brain Tumor from MR Images

4. Automatic Segmentation of Medical Images Using Fuzzy c-Means and the Genetic Algorithm

5. Comparison of Two Segmentation Methods for Mammographic Image

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1. A comparative study of breast tumour detection using a semantic segmentation network coupled with different pretrained CNNs;Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization;2024-07-07

2. An improved semantic segmentation for breast lesion from dynamic contrast enhanced MRI images using deep learning;International Journal of Imaging Systems and Technology;2024-01

3. Automated 3D Tumor Segmentation From Breast DCE-MRI Using Energy-Tuned Minimax Optimization;IEEE Access;2024

4. Exploration and Enhancement of Classifiers in the Detection of Lung Cancer from Histopathological Images;Diagnostics;2023-10-23

5. Breast Lesion Segmentation in DCE- MRI Imaging;2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS);2018-11

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