Artificial Intelligence on Medical Data: Proceedings of International Symposium, ISCMM 2021

This book summarizes the presentations and discussions from the Second International Symposium on Computer Vision and Machine Intelligence in Medical Image Analysis (ISCMM 2021), highlighting common research problems and challenges in medical image analysis, including deep learning methods, and their applications in various areas such as lung and chest x-ray, breast CAD, microscopy, and pathology.

Format: Hardback
Length: 484 pages
Publication date: 24 July 2022
Publisher: Springer Verlag, Singapore

This book is a comprehensive collection of high-quality papers presented at the Second International Symposium on Computer Vision and Machine Intelligence in Medical Image Analysis (ISCMM 2021), organized by the Computer Applications Department, SMIT, in collaboration with the Department of Pathology, SMIMS, Sikkim, India, and funded by the Indian Council of Medical Research. The symposium was held from 11 to 12 November 2021, and it brought together experts from various fields to discuss common research problems and challenges in medical image analysis.

One of the key topics of the symposium was the application of deep learning methods in medical image analysis. Deep learning is a powerful tool that has revolutionized the field of computer vision by enabling machines to learn complex patterns and make accurate predictions. In the medical domain, deep learning has been used to detect and classify medical images, such as X-rays, CT scans, and MRI images. The studies included in this book demonstrate how deep learning can be used to improve the accuracy and efficiency of medical image analysis, particularly in the areas of lung and chest x-ray, breast CAD, microscopy, and pathology.

Another important aspect of the symposium was the discussion of how these theories can be applied to a broad range of application areas. Medical image analysis is not limited to a single field, and the insights gained from this research can be used in many other domains, such as healthcare, agriculture, and environmental science. The studies included in this book showcase the potential of medical image analysis to address real-world problems and improve the lives of people around the world.

The studies included in this book mainly focus on the detection of events from biomedical signals. Biomedical signals are the electrical signals generated by the body's organs and tissues, and they can be used to detect and diagnose a wide range of medical conditions. The studies in this book demonstrate how deep learning can be used to analyze biomedical signals and extract meaningful information that can be used to improve patient care.

In conclusion, this book is a valuable resource for researchers and practitioners in the field of medical image analysis. It provides a comprehensive overview of the latest research trends and challenges in the field, and it showcases the potential of deep learning and other advanced technologies to improve the accuracy and efficiency of medical image analysis. The studies included in this book are a testament to the hard work and dedication of the researchers who contributed to the symposium, and they will undoubtedly inspire future research in this area.

Introduction:
The Second International Symposium on Computer Vision and Machine Intelligence in Medical Image Analysis (ISCMM 2021) was a groundbreaking event that brought together experts from around the world to discuss the latest advancements in medical image analysis. The symposium was organized by the Computer Applications Department, SMIT, in collaboration with the Department of Pathology, SMIMS, Sikkim, India, and funded by the Indian Council of Medical Research. The event was held from 11 to 12 November 2021, and it was attended by researchers, practitioners, and students from various fields, including computer science, medicine, and healthcare.

Highlights of the Symposium:
One of the key highlights of the symposium was the presentation of high-quality papers that covered a wide range of topics related to medical image analysis. The papers presented at the symposium addressed common research problems and challenges in the field, such as the detection of events from biomedical signals, the development of automated diagnosis systems, and the analysis of large medical datasets. The symposium also provided an opportunity for researchers to showcase their latest findings and technologies, and it facilitated discussions and collaborations among experts from different fields.

Application of Deep Learning Methods in Medical Image Analysis:
Deep learning is a powerful tool that has revolutionized the field of computer vision by enabling machines to learn complex patterns and make accurate predictions. In the medical domain, deep learning has been used to detect and classify medical images, such as X-rays, CT scans, and MRI images. The studies included in this book demonstrate how deep learning can be used to improve the accuracy and efficiency of medical image analysis, particularly in the areas of lung and chest x-ray, breast CAD, microscopy, and pathology.

One of the key challenges in medical image analysis is the high volume of data that needs to be processed. Deep learning algorithms can handle large amounts of data and can extract meaningful information from it. The studies in this book demonstrate how deep learning can be used to analyze biomedical signals and extract meaningful information that can be used to improve patient care.

Another important aspect of the symposium was the discussion of how these theories can be applied to a broad range of application areas. Medical image analysis is not limited to a single field, and the insights gained from this research can be used in many other domains, such as healthcare, agriculture, and environmental science. The studies included in this book showcase the potential of medical image analysis to address real-world problems and improve the lives of people around the world.

Conclusion:
The Second International Symposium on Computer Vision and Machine Intelligence in Medical Image Analysis (ISCMM 2021) was a successful event that brought together
together experts from various fields to discuss the latest advancements in medical image analysis. The symposium provided a valuable platform for researchers, practitioners, and students to showcase their latest findings and technologies, and it facilitated discussions and collaborations among experts from different fields. The studies included in this book are a testament to the hard work and dedication of the researchers who contributed to the symposium, and they will undoubtedly inspire future research in this area.

Weight: 904g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811901508
Edition number: 1st ed. 2023