Book[edited by] K.C. Santosh, Sameer Antani, D.S. Guru, Nilanjan Dey.
Summary: The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.
Contents:
Preface
Editors
1. A novel stacked model ensemble for improved TB detection in chest radiographs
2. The role of artificial intelligence (AI) in medical imaging: general radiologic and urologic applications
3. Early detection of epileptic seizures based on scalp EEG signals
4. Fractal analysis in histology classification of non-small cell lung cancer
5. Multi-feature-based classification of osteoarthritis in knee joint X-ray images
6. Detection and classification of non-proliferative diabetic retinopathy lesions
7. Segmentation and analysis of CT images for bone fracture detection and labeling
8. A systematic review of 3D imaging in biomedical applications
9. Review on the evolution of comprehensive information for digital sliding of pathology and medical image segmentation
10. Pathological medical image segmentation: a quick review based on parametric techniques
Index.