Yuliana Jiménez-Gaona, María José Rodríguez-Álvarez, Diana Carrión-Figueroa, Darwin Castillo-Malla, Vasudevan Lakshminarayanan
{"title":"利用卷积神经网络和迁移学习对乳房X光照片中的乳房肿块区域进行分类。","authors":"Yuliana Jiménez-Gaona, María José Rodríguez-Álvarez, Diana Carrión-Figueroa, Darwin Castillo-Malla, Vasudevan Lakshminarayanan","doi":"10.1080/09500340.2024.2313724","DOIUrl":null,"url":null,"abstract":"This study introduces a novel approach aimed at enhancing the quality of digital mammography images through pre-processing techniques, to improve breast cancer detection accuracy. The primary objec...","PeriodicalId":16426,"journal":{"name":"Journal of Modern Optics","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Breast mass regions classification from mammograms using convolutional neural networks and transfer learning.\",\"authors\":\"Yuliana Jiménez-Gaona, María José Rodríguez-Álvarez, Diana Carrión-Figueroa, Darwin Castillo-Malla, Vasudevan Lakshminarayanan\",\"doi\":\"10.1080/09500340.2024.2313724\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study introduces a novel approach aimed at enhancing the quality of digital mammography images through pre-processing techniques, to improve breast cancer detection accuracy. The primary objec...\",\"PeriodicalId\":16426,\"journal\":{\"name\":\"Journal of Modern Optics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2024-02-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Modern Optics\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1080/09500340.2024.2313724\",\"RegionNum\":4,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"OPTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Modern Optics","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1080/09500340.2024.2313724","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPTICS","Score":null,"Total":0}
引用次数: 0
摘要
本研究介绍了一种新方法,旨在通过预处理技术提高数字乳腺 X 射线图像的质量,从而提高乳腺癌检测的准确性。研究的主要目标是提高乳腺癌检测的准确性。
Breast mass regions classification from mammograms using convolutional neural networks and transfer learning.
This study introduces a novel approach aimed at enhancing the quality of digital mammography images through pre-processing techniques, to improve breast cancer detection accuracy. The primary objec...
期刊介绍:
The journal (under its former title Optica Acta) was founded in 1953 - some years before the advent of the laser - as an international journal of optics. Since then optical research has changed greatly; fresh areas of inquiry have been explored, different techniques have been employed and the range of application has greatly increased. The journal has continued to reflect these advances as part of its steadily widening scope.
Journal of Modern Optics aims to publish original and timely contributions to optical knowledge from educational institutions, government establishments and industrial R&D groups world-wide. The whole field of classical and quantum optics is covered. Papers may deal with the applications of fundamentals of modern optics, considering both experimental and theoretical aspects of contemporary research. In addition to regular papers, there are topical and tutorial reviews, and special issues on highlighted areas.
All manuscript submissions are subject to initial appraisal by the Editor, and, if found suitable for further consideration, to peer review by independent, anonymous expert referees.
General topics covered include:
• Optical and photonic materials (inc. metamaterials)
• Plasmonics and nanophotonics
• Quantum optics (inc. quantum information)
• Optical instrumentation and technology (inc. detectors, metrology, sensors, lasers)
• Coherence, propagation, polarization and manipulation (classical optics)
• Scattering and holography (diffractive optics)
• Optical fibres and optical communications (inc. integrated optics, amplifiers)
• Vision science and applications
• Medical and biomedical optics
• Nonlinear and ultrafast optics (inc. harmonic generation, multiphoton spectroscopy)
• Imaging and Image processing