使用深度稀疏波幅自编码器方法提高乳腺癌分类
Sarah A Alzakari1, Salima Hassairi2, Amel Ali Al Hussan1
1Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Scientific reports
|July 18, 2025
概括
一个新的Deep Sparse Wavelet自编码器 (DSWAE) 准确地对2D乳腺癌图像进行分类. 这种深度学习方法改善了早期检测和高精度分期良性,恶性和正常病例.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 计算生物学 计算生物学
背景情况:
- 对2D乳腺癌图像进行准确的分类对于早期检测和分期至关重要.
- 数字成像技术的进步需要改进的分类方法.
- 现有的方法在平衡精度和计算效率方面面临挑战.
研究的目的:
- 为2D乳腺癌图像引入一种新的分类方法.
- 开发一个强大的模型,整合深度学习,稀疏编码和波纹网络.
- 提高乳腺癌图像分析的分类准确性和计算效率.
主要方法:
- 开发了深度稀疏波形自编码器 (DSWAE) 架构.
- 在深度学习框架内集成堆叠的波列自动编码器.
- 使用深度网络,最小参数,以优化处理.
主要成果:
- DSWAE在良性病例中达到94.5%的精度,在恶性病例中达到93.8%.
- 良性病例的召回率为93.65%,恶性病例的召回率为96.2%.
- 对于正常情况下,实现了完美的100%精度率,超过了最先进的方法.
结论:
- DSWAE模型在2D乳腺癌图像分类中表现出卓越的性能.
- 拟议的架构提高了准确性和计算效率.
- 这种方法为早期乳腺癌检测和分期提供了有希望的进步.
关键词:
2D图像分析 两维图像分析自动编码器 自动编码器他打破了他的分手.乳腺癌分类 乳腺癌分类计算效率 计算效率 计算效率深度学习 (Deep Learning) 是一种深度学习.稀少的编码 稀少的编码波浪式网络 (wavelet network) 是一种波浪式网络.更多相关视频
06:03Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis
Published on: February 6, 2020
6.7K
15:48Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
22.6K
相关概念视频
01:30Classification of Signals
899
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
899
01:22Force Classification
1.6K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.6K