This book provides detailed practical applications of AI algorithms and illustrates how these algorithms can be used to improve the quality and efficiency for the diagnosis and treatment of brain gliomas. This book proposes an innovative framework of “fusion segmentation” collaborative optimization, aiming at the difficult cross-modal feature extraction and insufficient sensitivity to heterogeneous imaging in multimodal image fusion and segmentation is proposed in this book, which will also provide valuable reference for medical workers and graduate students. Researchers, engineers, and graduate students in the fields of medical management and software engineering constitute the primary readership.
This book is tailored to meet the information needs of professionals and students seeking in-depth insights into the intersection of medical management and software engineering.
This book provides detailed practical applications of AI algorithms and illustrates how these algorithms can be used to improve the quality and efficiency for the diagnosis and treatment of brain gliomas. This book proposes an innovative framework of “fusion segmentation” collaborative optimization, aiming at the difficult cross-modal feature extraction and insufficient sensitivity to heterogeneous imaging in multimodal image fusion and segmentation is proposed in this book, which will also provide valuable reference for medical workers and graduate students. Researchers, engineers, and graduate students in the fields of medical management and software engineering constitute the primary readership.
This book is tailored to meet the information needs of professionals and students seeking in-depth insights into the intersection of medical management and software engineering.
Shuli Guo
Multimodal MRI Fusion-Segmentation Algorithm Brain Glioma Brain Tumor Detection