Automated Segmentation of Abnormal Tissues in Medical Images

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Homayoun Hassan; EBRAHIMPOUR KOMLEH HOSSEIN

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Journal Paper

Paper Information

Journal: JOURNAL OF BIOMEDICAL PHYSICS AND ENGINEERING Year:2021 | Volume:11 | Issue:4 Page(s): 415-424

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Information Journal Paper

Title

Automated Segmentation of Abnormal Tissues in Medical Images

Author(s)

Homayoun Hassan | EBRAHIMPOUR KOMLEH HOSSEIN | Issue Writer Certificate

Keywords

Skin Abnormalities

Abnormal Tissue Detection

Multiple Sclerosis

Breast Cancer

Multiple Pulmonary Nodules

Automatic Segmentation

Medical Imaging

Abstract

Nowadays, medical image modalities are almost available everywhere. These modalities are bases of diagnosis of various diseases sensitive to specific tissue type. Usually physicians look for abnormalities in these modalities in diagnostic procedures. Count and volume of abnormalities are very important for optimal treatment of patients. Segmentation is a preliminary step for these measurements and also further analysis. Manual segmentation of abnormalities is cumbersome, error prone, and subjective. As a result, automated segmentation of abnormal tissue is a need. In this study, representative techniques for segmentation of abnormal tissues are reviewed. Main focus is on the segmentation of Multiple Sclerosis lesions, Breast Cancer masses, lung nodules, and skin lesions. As experimental results demonstrate, the methods based on deep learning techniques perform better than other methods that are usually based on handy feature engineering techniques. Finally, the most common measures to evaluate automated abnormal tissue segmentation methods are reported.

Cites

MMTDNN: Multi-View Massive Training Deep Neural Network for Segmentation and Detection of Abnormal Tissues in Medical Images

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APA: Copy

Homayoun, Hassan, & EBRAHIMPOUR KOMLEH, HOSSEIN. (2021). Automated Segmentation of Abnormal Tissues in Medical Images. JOURNAL OF BIOMEDICAL PHYSICS AND ENGINEERING, 11(4), 415-424. SID. https://sid.ir/paper/668311/en

Vancouver: Copy

Homayoun Hassan, EBRAHIMPOUR KOMLEH HOSSEIN. Automated Segmentation of Abnormal Tissues in Medical Images. JOURNAL OF BIOMEDICAL PHYSICS AND ENGINEERING[Internet]. 2021;11(4):415-424. Available from: https://sid.ir/paper/668311/en

IEEE: Copy

Hassan Homayoun, and HOSSEIN EBRAHIMPOUR KOMLEH, “Automated Segmentation of Abnormal Tissues in Medical Images,” JOURNAL OF BIOMEDICAL PHYSICS AND ENGINEERING, vol. 11, no. 4, pp. 415–424, 2021, [Online]. Available: https://sid.ir/paper/668311/en

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