D. Pasynkov, А.А. Kolchev, I. Egoshin, I.V. Klioushkin, О.О. Pasynkova
{"title":"超声图像中乳腺实体病灶及其周围区域的分割方法","authors":"D. Pasynkov, А.А. Kolchev, I. Egoshin, I.V. Klioushkin, О.О. Pasynkova","doi":"10.18287/2412-6179-co-1234","DOIUrl":null,"url":null,"abstract":"The paper proposes an approach to the segmentation of solid breast lesions and their peripheral areas in ultrasound images. It is noted that identifying the outermost breast lesion structures is an important step for the further lesion classification, directly affecting the final classification of its type. The main feature of the proposed approach is that its implementation takes into account peculiarities of pixel brightness variations in the original image, without using speckle noise filters. The method was tested on a set of ultrasound images of morphologically verified 42 benign and 49 malignant breast lesions marked by a radiologist. The segmentation results were compared with the results of manual marking performed by the radiologist. The average errors in the segmentation of benign and malignant lesion were 5 pixels – for the lesion area and 7 pixels – for the peripheral area, which is insignificant, taking into account the error of manual marking performed by radiologist (3.9 and 4.7 pixels, respectively). The average intersection-over-union (IoU) metrics were 0.82 and 0.80, respectively. The presented results indicate the possibility of using the developed technology in a combination with the system of lesion differentiation.","PeriodicalId":46692,"journal":{"name":"Computer Optics","volume":"45 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An approach to segmentation of a solid focal lesion in breast and its peripheral areas in ultrasound images\",\"authors\":\"D. Pasynkov, А.А. Kolchev, I. Egoshin, I.V. Klioushkin, О.О. Pasynkova\",\"doi\":\"10.18287/2412-6179-co-1234\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper proposes an approach to the segmentation of solid breast lesions and their peripheral areas in ultrasound images. It is noted that identifying the outermost breast lesion structures is an important step for the further lesion classification, directly affecting the final classification of its type. The main feature of the proposed approach is that its implementation takes into account peculiarities of pixel brightness variations in the original image, without using speckle noise filters. The method was tested on a set of ultrasound images of morphologically verified 42 benign and 49 malignant breast lesions marked by a radiologist. The segmentation results were compared with the results of manual marking performed by the radiologist. The average errors in the segmentation of benign and malignant lesion were 5 pixels – for the lesion area and 7 pixels – for the peripheral area, which is insignificant, taking into account the error of manual marking performed by radiologist (3.9 and 4.7 pixels, respectively). The average intersection-over-union (IoU) metrics were 0.82 and 0.80, respectively. The presented results indicate the possibility of using the developed technology in a combination with the system of lesion differentiation.\",\"PeriodicalId\":46692,\"journal\":{\"name\":\"Computer Optics\",\"volume\":\"45 1\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Optics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18287/2412-6179-co-1234\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"OPTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Optics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18287/2412-6179-co-1234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPTICS","Score":null,"Total":0}
An approach to segmentation of a solid focal lesion in breast and its peripheral areas in ultrasound images
The paper proposes an approach to the segmentation of solid breast lesions and their peripheral areas in ultrasound images. It is noted that identifying the outermost breast lesion structures is an important step for the further lesion classification, directly affecting the final classification of its type. The main feature of the proposed approach is that its implementation takes into account peculiarities of pixel brightness variations in the original image, without using speckle noise filters. The method was tested on a set of ultrasound images of morphologically verified 42 benign and 49 malignant breast lesions marked by a radiologist. The segmentation results were compared with the results of manual marking performed by the radiologist. The average errors in the segmentation of benign and malignant lesion were 5 pixels – for the lesion area and 7 pixels – for the peripheral area, which is insignificant, taking into account the error of manual marking performed by radiologist (3.9 and 4.7 pixels, respectively). The average intersection-over-union (IoU) metrics were 0.82 and 0.80, respectively. The presented results indicate the possibility of using the developed technology in a combination with the system of lesion differentiation.
期刊介绍:
The journal is intended for researchers and specialists active in the following research areas: Diffractive Optics; Information Optical Technology; Nanophotonics and Optics of Nanostructures; Image Analysis & Understanding; Information Coding & Security; Earth Remote Sensing Technologies; Hyperspectral Data Analysis; Numerical Methods for Optics and Image Processing; Intelligent Video Analysis. The journal "Computer Optics" has been published since 1987. Published 6 issues per year.