08051nam a2200649 i 45000010014000000030004000140050017000180060019000350070015000540080041000690200025001100200024001350200025001590200027001840240035002110350025002460350022002710400040002930500035003330600031003680720016003990720023004152450118004382640098005563000071006543360021007253370026007463380032007724900027008044900034008315000043008655040041009085051701009495201289026505210208039395300029041475380036041765380078042125452490042905880059067806500041068396500037068806500021069176500023069386500024069616500019069856500023070046500036070276500052070637000029071157000030071447100054071747760049072288300031072778300034073088560059073429780750323529IOP20251030124212.0m    eo  d        cr cn |||m|||a240104s2023    enka   fob    000 0 eng d  a9780750323529qebook  a9780750323512qmobi  z9780750323505qprint  z9780750323536qmyPrint7 a10.1088/978-0-7503-2352-92doi  a(CaBNVSL)thg00083723  a(OCoLC)1416752696  aCaBNVSLbengerdacCaBNVSLdCaBNVSL 4aRC78.7.D53bM855 2022eb vol. 2 4aWN 180bM961 2022eb vol. 2 7aMQW2bicssc 7aTEC0590002bisacsh00aMultimodality imaging.nVolume 2,pHeart, lungs and peripheral organs /cedited by Mainak Biswas, Jasjit S. Suri. 1aBristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) :bIOP Publishing,c[2023]  a1 online resource (various pagings) :billustrations (some color).  atext2rdacontent  aelectronic2isbdmedia  aonline resource2rdacarrier1 a[IOP release $release]1 aIOP ebooks. [2023 collection]  a"Version: 20231101"--Title page verso.  aIncludes bibliographical references.0 apart I. An overview of deep learning and its applications in COVID-19 and tuberculosis. 1. An overview of AI applications in medical imaging for COVID-19-related brain and heart injuries / Harshit Sharma, Radhakrishn Birla, Mainak Biswas and Jasjit S. Suri -- 2. Characterizing acute respiratory distress syndrome in COVID-19 : a narrative review of artificial intelligence-based lung analysis / Ashutosh Jha, Radhakrishn Birla, Mainak Biswas and Jasjit S. Suri -- 3. A multicenter study using COVLIAS 2.0 : eight pruned deep learning models for efficient COVID-19 CT lung segmentation and lesion localization / Venkateshh Moningi, Mohit Agarwal, Mainak Biswas and Jasjit S. Suri -- 4. An investigation of the inter-variability in COVLIAS 1.0 : hybrid deep learning approaches for segmenting COVID-19 lungs in CT scans / Venkateshh Moningi, Sushant Agarwal, Mainak Biswas and Jasjit S. Suri -- 5. A comparative analysis of tuberculosis-infected lung x-ray image segmentation : U-Net vs. U-Net++ / Radhakrishn Birla, Gautam Chugh, Swastika Bishnoi, Riddhika Shringi, Piyush Kumar and Mainak Biswas -- part II. 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 / Mayank Singhal, Radhakrishn Birla, Mainak Biswas, Sujoy Datta and Jasjit S. Suri -- 7. A deep learning perspective in internal carotid artery and bulb segmentation : review / Amita Banerjee, Pankaj Kumar Jain, Radhakrishn Birla, Mainak Biswas and Jasjit S. Suri -- 8. Deep learning framework for ultrasound-based carotid artery disease management : a review / Mainak Biswas and Jasjit S. Suri.3 aThis 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.  aAcademic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis.  aAlso available in print.  aMode of access: World Wide Web.  aSystem requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.  aMainak Biswas, PhD, 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 PhD 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 PhD 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., AtheroPoint(Tm), 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.0 aTitle from PDF title page (viewed on January 4, 2024). 0aDiagnostic imagingxData processing. 0aDeep learning (Machine learning) 0aComputer vision. 0aVisual perception.12aDiagnostic Imaging.12aDeep Learning.12aVisual Perception. 7aBiomedical engineering.2bicssc 7aTECHNOLOGY & ENGINEERING / Biomedical.2bisacsh1 aBiswas, Mainak,eeditor.1 aSuri, Jasjit S.,eeditor.2 aInstitute of Physics (Great Britain),epublisher.08iPrint version:z9780750323505z9780750323536 0aIOP (Series).pRelease 23. 0aIOP ebooks.p2023 collection.40uhttps://iopscience.iop.org/book/edit/978-0-7503-2352-9