"Over the last decades, there has been a revolution in the analysis of medical images with the new technological advancements. Innovative intelligent technologies have been developed to analyze and interpret medical images automatically for diseases diagnosis and disease assessment and for combatting new diseases. This new volume explores the latest cutting-edge research in medical image analysis. The advanced intelligent technologies discussed include machine learning, ensemble methods in machine learning, deep learning methods and firebase technology, infrared thermography, deep convolution neural networks, and more. Some of the specific uses of these technologies include for brain tumor MRIs, for breast cancer screening, for polycystic ovary syndrome classification, for detecting and monitoring Alzheimer's disease, for monitoring of newborns, for retinal disease diagnosis, for Covid-19 detection, and more. Key features: Covers the application of deep learning techniques for the medical image problems; Considers the development of future machine learning techniques and further applications of existing techniques; Presents literature reviews on deep learning methods for medical image analysis; Discusses the applications of applied intelligence for the diagnosis of medical images, image genomics, and brain connectomics; Relays the latest technologies and algorithms related to the state-of-the-art medical image analysis in assessing and diagnosing diseases. Applied Intelligence for Medical Image Analysis will be of interest to academics and researchers in the area of deep learning and medical imaging."-- Provided by publisher.

A Comparative Study of Anisotropic Diffusion Filters for Medical Image Denoising / Amira Hadj Fredj, Jihene Malek, and Souhir Mabrouk -- Salt-and-Pepper Noise Removal Techniques for Medical -- Image Reconstruction / Vatsal Nanda, Prateek Jeet Singh Sohi, Bharat Garg, and Prashant Singh Rana -- Comparative Analysis of PSO and WOA-Based Segmentation of Brain Tumor MRIs / Reena Tripathi and Bindu Verma -- Breast Cancer Screening Using Fractal Dimension of Chromatin in Interphase Nuclei of Buccal Epithelium / Dmitriy Klyushin, Kateryna Golubeva, Natalia Boroday, and Chan Kha Vu -- Polycystic Ovary Syndrome Classification Based on Machine Learning Techniques : A Comparative Analysis / Nancy Girdhar, Priya Singh, and Tisha Singhal -- A Comprehensive Review on Diagnosis of Alzheimer's Disease Using Ensemble Methods and Machine Learning / Prachi Patil and Sujata Kadu -- A New Strategy for the Prediction of Diabetic Retinopathy Using Deep Learning Methods and Firebase Technology / Abdelwaheb Jebnouni, Amira Hadj Fredj, and Jihene Malek -- Contactless Monitoring in Newborns Using Infrared Thermography : A Review / Lalit Maurya, Roop Singh, Deepak Chawla, and Prasant Mahapatra -- Retinal Disease Diagnosis Using Machine Learning Techniques / G. Kalaiarasi, B. Saritha, S. K. Kabilesh, and D. Mohanapriya -- Automated Segregation of Lymphoid and Myeloid Blasts in Acute Leukemia Cases Using a Deep Convolutional Neural Network / K. K. Anilkumar, V. J. Manoj, and T. M. Sagi -- Evaluation of Deep Learning Network Architectures for Medicine Expenditure Prediction in the Healthcare Domain / Ulises Manuel Ramirez-Alcocer, Jaciel David Hernandez-Resendiz, and Edgar Tello Leal -- COVID-19 Detection from Chest X-Ray Using a Customized Artificial Neural Network / Vinayak Tiwari, Amit Singhal, and Nischay Dhankhar -- An Automated Deep Learning Approach to Classify ECG Signals Using AlexNet / Neelofer Shaheen, Mudassir Hasan Khan, and Mohammad Sarfraz -- MLO and CC View of Feature Fusion and Mammogram Classification Using a Deep Convolution Neural Network / V. Sridevi and J. Abdul Samath.

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