The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Medical Imaging and Radiology in Explainable Deep Learning
|
|
Author(s): Kuldeep Singh Kaswan (Galgotias University, India)
Copyright: 2024
Pages: 21
Source title:
Machine and Deep Learning Techniques for Emotion Detection
Source Author(s)/Editor(s): Mritunjay Rai (Department of Electrical and Electronics Engineering, Shri Ramswaroop Memorial University, India)and Jay Kumar Pandey (Department of Electrical and Electronics Engineering, Shri Ramswaroop Memorial University, India)
DOI: 10.4018/979-8-3693-4143-8.ch011
Purchase
|
Abstract
This chapter delves into the intricacies of medical imaging and ultrasound, where interpretable deep learning methodologies emerge as invaluable tools. It elucidates the utilization of deep learning models to extract radiomic features, discern their clinical significance, and various methodologies for incorporating them into structures that are comprehensible. The study underscores the criticality of comprehending radiomic features and their pivotal role in facilitating accurate diagnoses and informed treatment decisions. The primary objective of this chapter is to attain an intricate understanding of deep learning methodologies tailored explicitly for healthcare AI, with a focal point on radiologists and medical images.
Related Content
|
G. Boopathy, Balaji Ganesan, P. Sivaprakasam, T. Kumaran.
© 2026.
42 pages.
|
|
G. Prasad.
© 2026.
14 pages.
|
|
Kishorebabu Dasari, Sujana Parry, Srinivas Mekala.
© 2026.
30 pages.
|
|
Chikesh Ranjan, Jonnalagadda Srinivas, P. S. Balaji, Kaushik Kumar.
© 2026.
24 pages.
|
|
G. Ananthi, S. Mehala Shevani, P. Priyadharshini Devi.
© 2026.
24 pages.
|
|
G. Prasad, Snehal Malik, Aadya Gupta, Yash Nigam.
© 2026.
26 pages.
|
|
Dhirendra Patel, M. L. Azad.
© 2026.
36 pages.
|
|
|