Cancer’s Probability Assessment from Breast Ultrasonograhys by Using Image Processing

DOI

10.2991/978-94-6463-208-8_3How to use a DOI?

Keywords

image processing; breast ultrasonography; KNN

Abstract

In Indonesia, breast cancer is the first leading cause of death in women. Even data from the WHO, shows that in 2020, from total of 213,000 cancer cases, there are 65,000 cases of breast cancer or about 30% of all cancer cases in women. Breast ultrasonograhy (BUS) is an effective way to detect cancer. In addition, BUS can distinguish benign and malignant, so it can reduce unnecessary biopsy procedure. Cancer’s probability assessment is necessary to examine by radiologist. One of the standard assessment is breast imaging-reporting and data system (BI-RADS). Radiologist use this standard from BUS to grade the cancer’s probability manually, so the result might be subjective. This research offered a new approach to standardize the system of cancer’s probability assessment by image processing. The proposed methods in this research begin with the pre-processing. The BUS images have been improved by image filtering and enhancing. After pre-processing, the cancer’s probability part has been segmented by semi-automatic methods. The manual method uses for locate cancer’s probability part roughly. The automatic method uses for segment the area of cancer. After that, the feature area of cancer has been extracted. The K-nearest neighbors (KNN) algorithm then used to classify the cancer’s probability according the BI-RADS. The proposed method produces 0.79 in Cohen’s kappa coefficient. This number indicates the system has substantial agreement with radiologist assessment.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Agwin Fahmi Fahanani
AU  - Habiba Aurora
AU  - Maskuril Barkah
AU  - Irma Darinafitri
AU  - Yuyun Yueniwati
PY  - 2023
DA  - 2023/06/26
TI  - Cancer’s Probability Assessment from Breast Ultrasonograhys by Using Image Processing
BT  - Proceedings of the International Conference of Medical and Life Science (ICoMELISA 2021)
PB  - Atlantis Press
SP  - 9
EP  - 13
SN  - 2468-5739
UR  - https://doi.org/10.2991/978-94-6463-208-8_3
DO  - 10.2991/978-94-6463-208-8_3
ID  - Fahanani2023
ER  -