Breast cancer is a leading cause of mortality among women, underscoring the critical need for accurate and early diagnosis to enhance treatment efficacy. Traditional imaging techniques are limited in their ability to differentiate between benign and malignant lesions, particularly in the early stages, for there are very few images available for the lesion area and the resolution of these images is poor. This paper introduces a novel lesion diffusion model that dynamically amplifies lesion areas, providing a multi-frame analysis to improve classification accuracy. By integrating time-aware motion modeling, the proposed method tracks temporal changes in lesions, Generating a sequence of magnified frames highlighting subtle lesion features. Tested on the BUSI breast ultrasound dataset, our model achieved a 10.269% improvement in classification accuracy over baseline methods, with an average gain of 4.645% across multiple frames. The results demonstrate the model's ability to enhance the claim and diagnostic utility of breast cancer images after magnification This dynamic lesion amplification approach presents a significant advancement in computer-aided breast cancer diagnostics, offering new possibilities for improving early-stage detection.

Yinyi Lai

Yifan Liu

Qiwen Zhang

Jiaqi Shang

Xinyi Qiu

Jun Yan

Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization is an international journal whose main goals are to promote solutions of excellence for both imaging and visualization of biomedical data, and establish links among researchers, clinicians, the medical technology sector and end-users.    The journal provides a comprehensive forum for discussion of the current state-of-the-art in the scientific fields related to imaging and visualization, including, but not limited to:    Applications of Imaging and Visualization  Computational Bio- imaging and Visualization  Computer Aided Diagnosis, Surgery, Therapy and Treatment  Data Processing and Analysis  Devices for Imaging and Visualization  Grid and High Performance Computing for Imaging and Visualization  Human Perception in Imaging and Visualization  Image Processing and Analysis  Image-based Geometric Modelling  Imaging and Visualization in Biomechanics  Imaging and Visualization in Biomedical Engineering  Medical Clinics  Medical Imaging and Visualization  Multi-modal Imaging and Visualization  Multiscale Imaging and Visualization  Scientific Visualization  Software Development for Imaging and Visualization  Telemedicine Systems and Applications  Virtual Reality  Visual Data Mining and Knowledge Discovery.

Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization is an international journal aimed at promoting excellent solutions for the imaging and visualization of biomedical data, while establishing connections among researchers, clinicians, the medical technology sector, and end-users. The journal provides a comprehensive forum for discussing the current state-of-the-art in scientific fields related to imaging and visualization, including but not limited to: Applications of Imaging and Visualization, Computational Bio-imaging and Visualization, Computer-Aided Diagnosis, Surgery, Therapy, and Treatment, Data Processing and Analysis, Devices for Imaging and Visualization, Grid and High-Performance Computing for Imaging and Visualization, Human Perception in Imaging and Visualization, Image Processing and Analysis, Image-based Geometric Modeling, Imaging and Visualization in Biomechanics, Imaging and Visualization in Biomedical Engineering, Medical Clinics, Medical Imaging and Visualization, Multi-modal Imaging and Visualization, Multiscale Imaging and Visualization, Scientific Visualization, Software Development for Imaging and Visualization, Telemedicine Systems and Applications, Virtual Reality, and Visual Data Mining and Knowledge Discovery.

《Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization》是一本国际期刊，旨在促进生物医学数据成像和可视化领域的卓越解决方案，并建立研究人员、临床医生、医疗技术行业和最终用户之间的联系。该期刊为讨论与成像和可视化相关的科学领域的最新进展提供了一个全面的平台，包括但不限于：成像和可视化的应用、计算生物成像和可视化、计算机辅助诊断、手术、治疗和护理、数据处理和分析、成像和可视化设备、成像和可视化的网格和高性能计算、人类在成像和可视化中的感知、图像处理和分析、基于图像的几何建模、生物力学中的成像和可视化、生物医学工程中的成像和可视化、医学诊所、医学成像和可视化、多模态成像和可视化、多尺度成像和可视化、科学可视化、成像和可视化的软件开发、远程医疗系统和应用、虚拟现实、视觉数据挖掘和知识发现。

Lesiondiff: enhanced breast cancer classification via dynamic lesion amplification using diffusion models

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Journal Info

Category	Quartile
ENGINEERING, BIOMEDICAL	4