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- 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.Digital Access TandFonline 2020 - ArticleLandau H, Adin I, Spitz IM.Isr J Med Sci. 1978 Jul;14(7):785-9.A 32-year-old man developed panhypopituitarism and diabetes insipidus shortly after sustaining a head injury. Hormonal investigation showed that basal prolactin levels were moderately elevated the first two years after the accident, but later returned to normal. There was no rise in prolactin after administration on chlorpromazine, and the response to thyrotropin-releasing hormone was attenuated. Basal luteinizing hormone and follicle-stimulating hormone levels were low and there was no change after administration of luteinizing-hormone-releasing hormone. There was also no growth hormone elevation following arginine infusion. On the other hand, there was a normal but delayed elevation of thyrotropin in response to thyrotropin-releasing hormone. Appropriate stimulation tests showed normal responsiveness of the thyroid, adrenals and testes. These findings are compatible with an injury to the pituitary stalk, damaging the neurohypophyseal tract and affecting the blood supply to the pituitary gland.