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Hybrid Machine Intelligence for Medical Image Analysis, 1st ed. 2020 Studies in Computational Intelligence Series, Vol. 841

Langue : Anglais

Coordonnateurs : Bhattacharyya Siddhartha, Konar Debanjan, Platos Jan, Kar Chinmoy, Sharma Kalpana

Couverture de l’ouvrage Hybrid Machine Intelligence for Medical Image Analysis

The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.

Preface.- Introduction.- Brain Tumor Segmentation from T1 Weighted MRI Images Using Rough Set Reduct and Quantum Inspired Particle Swarm Optimization.- Automated Region of Interest detection of Magnetic Resonance (MR) images by Center of Gravity (CoG).- Brain tumors detection through low level features detection and rotation estimation.- Automatic MRI Image Segmentation for Brain tumors detection using Multilevel Sigmoid Activation (MUSIG) function.- Automatic Segmentation of pulmonary nodules in CT Images for Lung Cancer detection using self-supervised Neural Network Architecture.- A Hierarchical Fused Fuzzy Deep Neural Network for MRI Image Segmentation and Brain Tumor Classification.- Computer Aided Detection of Mammographic Lesions using Convolutional Neural Network (CNN).- Conclusion.

Siddhartha Bhattacharyya completed his Ph.D. in Computer Science and Engineering at Jadavpur University, India, in 2008. Currently he is the Principal of RCC Institute of Information Technology, Kolkata, India. In addition, he is a Professor of Computer Application and Dean (Research and Development) of the institute. He served as the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence (IJACI), published by IGI Global. He is the Associate Editor of the International Journal of Pattern Recognition Research, IEEE Access, Evolutionary Intelligence and a member of Applied Soft Computing editorial board. His research interests include soft computing, pattern recognition, hybrid intelligence and quantum computing, and he has published over 230 research articles and patents.

Debanjan Konar is an Assistant Professor at the Department of Computer Science and Engineering at Sikkim Manipal Institute of Technology, India. He is pursuing his Ph.D. at the Indian Institute of Technology, Delhi in Quantum Inspired Soft Computing. His research interests include quantum inspired soft computing, deep learning, machine learning, and natural language processing. He has published several papers in these areas in leading journals and IEEE international conferences. He is also a reviewer for various international journals and conferences.

Chinmoy Kar is an Assistant Professor at the Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, and is pursuing his Ph.D. in Image Recognition at the Maulana Abul Kalam Azad University of Technology. His research interests include image processing and computational intelligence, and he actively publishes in these areas.

Kalpana Sharma is a Professor and Head of the Department of Computer Science and Engineering at SMI. She completed her Ph.D. Wireless Sensor Network Security at Manipal University in 2011. Her research interests include wir

Covers a broad range of potential machine learning and computational intelligence paradigms for medical image analysis Includes an in-depth analysis of hybrid machine intelligence supported by real-world examples Supplemented by coding examples and video demonstrations for each chapter

Date de parution :

Ouvrage de 293 p.

15.5x23.5 cm

Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).

105,49 €

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Date de parution :

Ouvrage de 293 p.

15.5x23.5 cm

Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).

105,49 €

Ajouter au panier