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Applications of Artificial Intelligence in Medical Imaging

Provides updated knowledge on the applications of artificial intelligence in medical image analysis

Abdulhamit Subasi (Edited by)

9780443184505

Paperback / softback, published 11 November 2022

380 pages
23.4 x 19 x 2.4 cm, 0.77 kg

Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound. The book discusses the use of AI for detection of several cancer types, including brain tumor, breast, pancreatic, rectal, lung colon, and skin. In addition, it explains how AI and deep learning techniques can be used to diagnose Alzheimer's, Parkinson's, COVID-19 and mental conditions.

This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about AI and its impact in medical/biomedical image analysis.

1. Introduction to artificial intelligence techniques for medical image analysis

ABDULHAMIT SUBASI

2. Lung cancer detection from histopathological lung tissue images using deep learning

AAYUSH RAJPUT AND ABDULHAMIT SUBASI

3. Magnetic resonance imagining-based automated brain tumor detection using deep learning techniques

ABHRANTA PANIGRAHI AND ABDULHAMIT SUBASI

4. Breast cancer detection from mammograms using artificial intelligence

ABDULHAMIT SUBASI, AAYUSH DINESH KANDPAL, KOLLA ANANT RAJ AND ULAS BAGCI

5. Breast tumor detection in ultrasound images using artificial intelligence

OMKAR MODI AND ABDULHAMIT SUBASI

6. Artificial intelligence-based skin cancer diagnosis

ABDULHAMIT SUBASI AND SAQIB AHMED QURESHI

7. Brain stroke detection from computed tomography images using deep learning algorithms

AYKUT DIKER, ABDULLAH ELEN AND ABDULHAMIT SUBASI

8. A deep learning approach for COVID-19 detection from computed tomography scans

ASHUTOSH VARSHNEY AND ABDULHAMIT SUBASI

9. Detection and classification of Diabetic Retinopathy Lesions using deep learning

SIDDHESH SHELKE AND ABDULHAMIT SUBASI

10. Automated detection of colon cancer using deep learning

AAYUSH RAJPUT AND ABDULHAMIT SUBASI

11. Brain hemorrhage detection using computed tomography images and deep learning

ABDULLAH ELEN, AYKUT DIKER AND ABDULHAMIT SUBASI

12. Artificial intelligence-based retinal disease classification using optical coherence tomography images

SOHAN PATNAIK AND ABDULHAMIT SUBASI

13. Diagnosis of breast cancer from histopathological images with deep learning architectures

EMRAH HANCER AND ABDULHAMIT SUBASI

14. Artificial intelligence based Alzheimer’s disease detection using deep feature extraction

MANAV NITIN KAPADNIS, ABHIJIT BHATTACHARYYA AND ABDULHAMIT SUBASI

Subject Areas: Medical bioinformatics [MBF]

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