This volume discusses various diseases related to lung, heart, peripheral arterial imaging, and miscellaneous topics like gene expression characterization and classification. Further, the Vol. 2 discusses imaging applications, their complexities and the DL-models employed to resolve them in detail. The DL-based applications are categorized into two types: segmentation and characterization.
The segmentation is chiefly involved in dissecting region-of-interest (ROI) of the infected part. In the characterization part, the dissected ROI or the overall image is graded as per the risk factor is involved. DL has a remarkable success in segmenting carotid plaque area from ultrasound common carotid artery images. Similarly in case of brain imaging, DL-based applications for brain cancer are divided into segmentation and characterization. In the segmentation part, the brain tumour is separated from the healthy tissue. In the characterization part, the tumour cells are graded as per their risk. Overall, DL is human brain comparable intelligence system which can strengthen effective medical treatment in a faster way. It is for sure, that DL-based technologies can enable doctors to quickly diagnose the patients, provide an effective plan for treatment and help in saving lives.
Key features:
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Discusses various diseases related to lung, heart, peripheral arterial imaging, and miscellaneous topics like gene expression characterization and classification
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Discusses imaging applications, their complexities and the DL-models employed to resolve them in detail
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Takes the most basic workable model and then builds the entire architecture in a bottom-up approach
- Provides state-of-the-art contributions while addressing doubts in multimodal research
- Details the future of deep leanring and big data in medical imaging
Table of Content
1: An Overview of AI Applications in Medical Imaging for COVID-19-Related Brain and Heart Injuries
2: Characterizing Acute Respiratory Distress Syndrome in COVID-19: A Narrative Review of Artificial Intelligence-based Lung Analysis
3: A multicenter study using COVLIAS 2.0: eight pruned deep learning models for efficient COVID-19 CT lung segmentation and lesion localization
4: An investigation of the inter-variability in COVLIAS 1.0: Hybrid deep learning approaches for segmenting COVID-19 lungs in CT scans
5: A Comparative Analysis of Tuberculosis-Infected Lung X-Ray Image Segmentation: UNet vs. UNet++
An overview of Deep Learning and its applications in cardiovascular diseases
6: Reviewing the Role of Artificial Intelligence in Heart and Vascular Ultrasound: Advancements and Applications
7: A Deep Learning Perspective in Internal Carotid Artery and Bulb Segmentation: Review
8: Deep Learning Framework for Ultrasound-based Carotid Artery Disease Management: A Review
About the author
Mainak Biswas, Ph D, computer scientist with specialization in application of machine learning and deep learning in biomedical domain. His research is inspired from providing an effective solution for computer aided diagnosis for diverse diseases. His Ph D specialization was in application of advanced machine learning and deep learning in complex tissue characterization and segmentation from ultrasound images of liver and carotid arteries.
His other interests are development of advanced machine learning architectures and early warning systems for risk estimation of both symptomatic and asymptomatic patients at high risk of CVDs. He has published and presented more than 35 papers in the area of characterization and segmentation of ultrasound images through machine and deep learning platforms. Dr. Mainak Biswas completed B.Tech from Government College of Engineering and Ceramic Technology under West Bengal University of Technology, Kolkata, M.Tech from Jadavpur University and Ph D from National Institute of Technology Goa, INDIA. Currently, he is serving as Associate Professor at Kalinga Institute of Industrial Technology, Bhubaneswar, INDIA.
Jasjit S. Suri, an innovator, a visionary, a scientist, and an internationally known world leader, has spent over 30 years in the field of biomedical engineering/sciences, software and hardware engineering and its management. During his career in biomedical industry/imaging, he has had an upstream growth and responsibilities from scientific engineer, scientist, manager, Director R&D, Sr. Director, Vice President, Chief Technology Officer (CTO), CEO level positions in industries like Siemens Medical Systems, Philips Medical Systems, Fisher Imaging Corporation and Eigen Inc., Global Biomedical Technologies Inc., Athero Point™, respectively and managed up to a maximum of 100 people.
Dr. Suri is a pioneer in the area of Computer Vision and Artificial Intelligence (AI), and has published over 1000+ International Journals covering several fields including 150+ articles in Vascular, Coronary, Prostate, Mammography, Diabetes, and COVID-19 CT lung area. Dr. Suri has conducted over 50 national and international seminars around the globe. He received his Masters from University of Illinois, Chicago, Doctorate from University of Washington, Seattle, and Masters in Business Administration (MBA) from Weatherhead School of Management, Case Western Reserve University (CWRU), Cleveland. He currently lives in California, USA.
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