An algorithm for automatic ROI generation for detection of breast tumors in ultrasound images
Publish place: 12th International Congress on Breast Cancer
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICBCMED12_117
تاریخ نمایه سازی: 2 تیر 1397
Abstract:
Introduction: Discovering early symptoms of breast cancer using clinical examination play a crucial role in mortality reduction. Among the available imaging modality breast ultrasound (BUS) is a key for early etection of breast malignancies. However, clinical experience and expert knowledge are necessary to achieve correct diagnosis. Recently breast ultrasound (BUS) Computer-aided diagnosis systems (CAD) systems have been introduces to overcome drawback of human perception-based diagnosis. Aims: One of the challenging problems for developing a CAD for BUS images is locating regions of interest (ROIs) automatically. This is because of complicated structure of breast and poor quality of ultrasound images. In this work, we propose an approach for performing accurate and robust ROI generation. Material & Methods: ROI generation was mainly based on image entropy and gradient. It includes three main steps first, preprocessing to speckle reduction, contrast enhancement and the removal of non-tumor edge using appropriate spatial filters second, calculating textural information entropy images and finally directional gradient. Result & Discussion: The proposed fully automatic segmentation method is applied to a BUS image and the performance is evaluated by the area and boundary error metrics. Compared with the manual ROI detection, the proposed method has comparable accuracy in segmenting BUS images. Conclusion: From the study result, it can be concluded that this algorithm is applicable in CAD baseddiagnostic of BUS images. Future work focuses on evaluating this algorithm on large set of database especially in more noisy BUS images with potentially multiple ROI numbers
Keywords:
breast tumor – ultrasound –image processing -ROI
Authors
Reza Reiazi
PhD Assistance Professor of Medical Physics, Department of Medical Physics, School of Medicine, Iran University of Medical Science, Tehran, Iran
Reza Paydar
PhD Assistance Professor of Medical Physics, Department of radiation sciences, School of Allied Medicine, Iran University of Medical Science, Tehran, Iran
Hamed Bagheri
MSc Radiation and Wave research center, AJA University of medical sciences,h.bagheri@ajaums.ac.ir
Maryam Etedadialiabadi
MS Radiology Department, Milad Hospital, Tehran, Iran