This book constitutes the proceedings of the First Workshop on Computational Mathematics Modeling in Cancer Analysis (CMMCA2022), held in conjunction with MICCAI 2022, in Singapore in September 2022. Due to the COVID-19 pandemic restrictions, the CMMCA2022 was held virtually. DALI 2022 accepted 15 papers from the 16 submissions that were reviewed. A major focus of CMMCA2022 is to identify new cutting-edge techniques and their applications in cancer data analysis in response to trends and challenges in theoretical, computational and applied aspects of mathematics in cancer data analysis.

Our second Research Topic in this series, Computational tools in inferring cancer tissue-of-origin and molecular classification towards personalized cancer therapy, Volume II (https://fro.ntiers.in/14361) has over 8 accepted articles and further manuscripts currently under review. Due to the continued success of these Research Topics and the interest in the subject, we will launch a third volume on the same topic. Inferring cancer tissue-of-origin and molecular classification are two critical problems in personalized cancer therapy. It is known that there are about 5% cancers of unknown primary (CUP) site. These kinds of patients are under empirical chemotherapy, which leads to a very low survival rate. Thus, it is important to infer cancer tissue-of-origin. However, experimental methods usually fail to identify the exact tissue-of-origin even after the death of a patient, which provides a need for computational methods especially in the era of big biomedical data. Based on the finding that gene expressions of metastasis cancer cells are more similar to those of original tissue than metastasis tissue, there have been a few computational methods developed in this area. However, the accuracy of the methods is yet to be improved to assure a clinical usage. In addition to CUP, inferring cancer tissue-of-origin is also important in avoiding misdiagnosis even if the cancer origin is known.

This book constitutes the refereed proceedings of two workshops held at the 18th International Conference on Computer Analysis of Images and Patterns, CAIP 2019, held in Salerno, Italy, in September 2019: First Workshop on Deep-learning based Computer Vision for UAV, DL-UAV 2019, and the First Workshop on Visual Computing and Machine Learning for Biomedical Applications, ViMaBi 2019. The 12 papers presented in this volume were carefully reviewed and selected from 16 submissions and focus on all aspects of visual computing and machine learning for biomedical applications, and deep-learning based computer vision for UAV.

This book discusses the role of nuclear medicine in the diagnosis, staging, and treatment of patients with specific cancers. It presents the incidence, pathophysiologic and clinical aspects of the disease, the use of nuclear imaging in diagnosis, staging requirements, management of specific tumors, and surveillance after primary treatment of cancers. It addresses the various diagnostic/therapeutic options that are currently available or are most likely to become available in the near future according to a prioritized approach, thereby keeping to a minimum the number of diagnostic imaging procedures the patient is expected to undergo. Topics include basic science, clinical applications, radionuclide therapy, radioguided surgery, heart disease in the cancer patient, and adverse effects of cancer therapy. Each clinical chapter discusses the radionuclide procedures within an integrated framework, thereby identifying the information required for effective treatment of specific tumors. The book concludes with a series of updated cases that define and expand the didactic material in the clinical application chapters. Thoroughly updated and revised, the third edition incorporates new clinical evidence validating the use of radionuclides for diagnosis and therapy in oncology, new radiotracers, and the growing integration of imaging modalities into different types of hybrid imaging. With contributions from a group of internationally distinguished practitioners, Nuclear Oncology: From Pathophysiology to Clinical Applications, Third Edition, is a valuable reference for nuclear medicine physicians, radiologists, medical and surgical oncologists, and other clinicians involved in the care and management of cancer patients.