Soft Computing Based Medical Image Analysis
Auteurs : Dey Nilanjan, Ashour Amira S., Shi Fuquian, Emilia Balas Valentina
Soft Computing Based Medical Image Analysis presents the foremost techniques of soft computing in medical image analysis and processing. It includes image enhancement, segmentation, classification-based soft computing, and their application in diagnostic imaging, as well as an extensive background for the development of intelligent systems based on soft computing used in medical image analysis and processing. The book introduces the theory and concepts of digital image analysis and processing based on soft computing with real-world medical imaging applications. Comparative studies for soft computing based medical imaging techniques and traditional approaches in medicine are addressed, providing flexible and sophisticated application-oriented solutions.
1. Medical image/signal processing theory and algorithms2. Computer-aided diagnosis, detection or surgery systems3. Medical informatics4. Medical video, image, or signal analysis5. Medical image motion analysis6. Evolutional medical image processing7. Hybrid soft computing approaches8. Medical video, image, or signal processing using soft computing techniques9. Medical image/signal acquisition theory, algorithms, or systems10. Soft computing techniques in the medical domain11. Genetic algorithms for medical applications12. Evolutionary computing for medical applications13. Application of medical image processing and soft computing application of image processing14. New trends and challenges in soft computing based medical imaging
Biomedical Engineers, Neural Engineers, scientific researchers, software developers, medical engineering designers, software/hardware medical device developers and engineers and technology developers
Nilanjan Dey is an Associate Professor in the Department of Computer Science and Engineering, Techno International New Town, Kolkata, India. He is a visiting fellow of the University of Reading, UK. He also holds a position of Adjunct Professor at Ton Duc Thang University, Ho Chi Minh City, Vietnam. Previously, he held an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He was awarded his PhD from Jadavpur University in 2015. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence , IGI Global, USA. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing (SpringerNature), Data-Intensive Research(SpringerNature), Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier). He was an associate editor of IET Image Processing and editorial board member of Complex & Intelligent Systems, Springer Nature. He is an editorial board member of Applied Soft Computing, Elsevier. He is having 35 authored books and over 300 publications in the area of medical imaging, machine learning, computer aided diagnosis, data mining, etc. He is the Fellow of IETE and Senior member of IEEE.
Amira S. Ashour is an Assistant Professor and Head of Electronics and Electrical Communications Engineering Department, Faculty of Engineering, Tanta University, Egypt. She is a member in the Research and Development Unit, Faculty of Engineering, Tanta University, Egypt. She received the B.Eng. degree in Electrical Engineering from Faculty of Engineering, Tanta University, Egypt in 1997, M.Sc. in Image Processing in 2001 and Ph.D. in Smart Antenna in 2005 from Faculty of Engineering, Tanta University, Egypt. Ashour has been the Vice Chair of Computer Engineering Department, Computers and Information Technology College, Taif University, KSA for one year from 2015. She has been the vice chair of CS department, CIT college, Taif University, KSA for 5 years. Her research interests a
- Covers numerous soft computing approaches, including fuzzy logic, neural networks, evolutionary computing, rough sets and Swarm intelligence
- Presents transverse research in soft computing formation from various engineering and industrial sectors in the medical domain
- Highlights challenges and the future scope for soft computing based medical analysis and processing techniques
Date de parution : 01-2018
Ouvrage de 292 p.
21.4x27.6 cm
Thèmes de Soft Computing Based Medical Image Analysis :
Mots-clés :
Approaches; Architecture; Artificial bee colony optimization; Artificial neural network (ANN); Brain tumor segmentation; Breast cancer; Breast density discrimination; Breast mass detection; Canny filter; CLAHE; Classification; Computed tomography; Convolutional neural network; Deep learning; Dempster-Shafer fusion; Despeckling; Diagnosis; Discrete wavelet transform; Disease; Early diagnosis; Edge detection; Edge-based structural similarity; Enhancement; Feature extraction; Fractal analysis; Gabor filter; Gaussian filtering; Genetic algorithm; Habitual smokerPlease check the inserted; and correct if necessary.-->; Histopathology; Hybrid speckle-reducing anisotropic diffusion; Image analysis; Image descriptors; Image segmentation; Kapur and Otsu criteria; Kernel learning; Laplacian filter; Laplacian of Gaussian filter; Laws' mask analysis; Local binary pattern; Magnetic resonance imaging; Medical image analysis; Medical image processing; Metaheuristics algorithms; MKL; Modified nonlinear complex diffusion; MRI; MRI images; Multiplicative speckle noises; Multithresholding; Neurofuzzy classifier; Oral cancer; Particle swarm optimization; PET; Please check if the suggested by the editor are appropriate; If not; please provide not more than 6-8 .-->; Biological; Prediction; Probabilistic neural network classifier; Prostate cancer diagnosis; Registration; Response prediction; Retinal disease; Retinal image; Retinal layers; Ribonucleic acid; Scout particle swarm optimization; Segmentation; SEM; Signal-to-noise ratio; Soft computing; Sonoelastography; Stationary wavelet transform; Support vector machine classifier; Texture analysis; Tissue