Author(s):
1. C. RAVINDRA MURTHY:
Electrical and Electronics Engineering department St. Peter's Institute of Higher Education and Research Avadi, Chennai
2. Dr. K. BALAJI:
Electrical and Electronics Engineering department St. Peter's Institute of Higher Education and Research Avadi, Chennai
Abstract:
Digital breast tomosynthesis (DBT) provides considerable benefits over digital mammography for radiologists in terms of cancer diagnosis. In earlier studies, conventional rapid analytical reconstruction techniques in DBT produced noisy images at constrained angles, causing the unconstrained recuperate issue. Consequently, architectural distortion (AD) detection might aid in the early detection of breast cancer, which is currently identified through a manual procedure. As a result, automated identification of AD remains underprivileged. To tackle these issues, a novel Unveil Architectural Distortion with Emendated Image in Digital Breast Tomosynthesis is proposed. To increase the image quality, the input image was first reconstructed using a scaled gradient projection algorithm in a model-based formulation. Following that, the unveil architectural distortion based on slicing process was incorporated to identify architectural distortion in the image. The suspicious spots were detected through a tracks-based trailing approach, and the advanced logistic regression classifier was employed to classify the malignant and benign spots. The results of the implementation show that the proposed approach is effective in detecting breast cancer.
Page(s):
3522-3534
DOI:
DOI not available
Published:
Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 11, Year: 2022
Keywords:
Digital Breast Tomosynthesis DBT
,
Scaled Gradient Projection SGP
,
Logistic Regression Classifier
,
Architectural Distortion AD
,
breast cancer
,
Slicing Process
References:
References are not available for this document.
Citations
Citations are not available for this document.