The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting. This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice. - An introduction to the concepts of radiomics - In-depth presentation of the core technologies and methods - Summary of current radiomics research, perspective on the future of radiomics and the challenges ahead - An introduction to several platforms that are planned to be built: cooperation, data sharing, software, and application platforms

In this issue, guest editors bring their considerable expertise to this important topic. - Contains 12 practice-oriented topics including adnexal mass imaging; radiomics and radiogenomics of ovarian cancer: implications for treatment monitoring and clinical management; imaging of cervical cancer; MRI of gynecologic tumors: pearls, pitfalls and tumor mimics; image-guided radiotherapy for gynecologic malignancies: what the radiologist needs to know; and more. - Provides in-depth clinical reviews on gynecologic malignancy, offering actionable insights for clinical practice. - Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.

This book constitutes the proceedings of the First International Workshop on Radiomics and Radiogenomics in Neuro-oncology, RNO-AI 2019, which was held in conjunction with MICCAI in Shenzhen, China, in October 2019. The 10 full papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with the development of tools that can automate the analysis and synthesis of neuro-oncologic imaging.

The year 2022 has been declared by the United Nations as the “International Year of Basic Sciences for Sustainable Development”. Sustainable development is focused on the UN’s 17 Sustainable Development Goals. These require the use of basic sciences. This edited book (volume 1) is a collection of twelve invited and peer-reviewed contributions from chemistry, materials science, energy applications, and artificial intelligence.

This issue of Neuroimaging Clinics of North America focuses on State of the Art Evaluation of the Head and Neck and is edited by Dr. Ashok Srinivasan. Articles will include: Diffusion MR in the head and neck: Principles and applications; Perfusion imaging in the head and neck: Go with the flow; MR spectroscopy of the head and neck: Principles, applications and challenges; Technological improvements in head and neck MR: At the cutting edge; Dual Energy CT in head and neck imaging: Pushing the envelope; Role of Ultrasound in head and neck evaluation; PET imaging in the head and neck: Current state and future directions; Patient centric head and neck cancer radiation therapy: Role of advanced imaging; AI in head and neck imaging: Glimpse into the future; NIRADS: Principles and implementation; Common data elements in head and neck reporting; and more!

The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book: Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methods Covers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformation Describes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentation Is aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering This is an essential reference for those looking to advance their understanding in this applied and emergent field.

This book aims to elucidate the current state of surgery for meningiomas of the posterior cranial fossa, seven decades after Professors Castellano and Ruggiero authored their book in 1953. The diagnosis and surgical treatment of these lesions posed an extraordinary challenge 70 years ago. In the words and descriptions of the 71 cases operated on by Olivecrona, each of us can still sense the emotion of someone venturing into unexplored terrain, striving to pave the way for those who would follow. Since 1953, thousands of meningiomas of the posterior cranial fossa have undergone surgery in Europe and around the world. This implies that many have traversed the path forged by Olivecrona in Europe and Cushing in the USA. While the road is now well-defined, our task today is to make this journey increasingly accessible. We must lay more stones on this path, illuminate it with lights, ensuring that no one loses their way. We cannot predict what the little path marked by Olivecrona and Erik Lindgren will become in another 70 years, but we hope for it to transform into a grand thoroughfare. A route that all neurosurgeons can navigate without losing their way, leading effortlessly and joyously to the singular goal we have always pursued: the health of our patients.