Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods

Diagnostic Biomedical Signal and Image Processing Applications: With Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities.

Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases.

《診斷生物醫學信號和影像處理應用：深度學習方法》提供了關於醫學影像和醫學信號分析的全面研究。本書討論了非侵入性方法（如腦電圖、心電圖、肌電圖、磁共振成像、功能性磁共振成像、電腦斷層掃描和X光等）的分類、分割、檢測、追蹤和檢索應用。這些影像和信號模態包含了當今醫學影像和醫學信號處理研究人員關注的主要主題。本書還強調去除噪音和指定數據集的關鍵特性，每一章節都包含了一個醫學影像或醫學信號模態的詳細內容。

本書專注於使用新的深度學習和卷積神經網絡方法解決真實的醫學問題，適合研究學者、研究生、教職員工、研發工程師和生物醫學工程師閱讀，他們希望了解醫學信號和影像在疾病早期診斷和治療中的重要作用。