Medical Data Assessment with Traditional, Machine-learning and Deeplearning Techniques-Reference-Cited by-同舟云学术

Medical Data Assessment with Traditional, Machine-learning and Deeplearning Techniques

Published:2021-01-12 Issue:10 Volume:16 Page:1185-1186
ISSN:1573-4056
Container-title:Current Medical Imaging Formerly Current Medical Imaging Reviews
language:en
Short-container-title:CMIR

Author:

Lin Hong¹,Satapathy Suresh Chandra²,Rajinikanth V.³

Affiliation:

1. College of Sciences & Technology, Computer Science & Engineering Technology, University of Houston-Downtown, Texas, United States

2. School of Computer Engineering, Kalinga Institute of Industrial Technology (Deemed to be University), Bhubaneswar- 751024, Odisha, India

3. Department of Electronics and Instrumentation Engineering, St. Joseph's College of Engineering, Chennai 600119, India

Publisher

Bentham Science Publishers Ltd.

Subject

Radiology, Nuclear Medicine and imaging

Reference10 articles.

1. Palani T.K.; Parvathavarthini B.; & Chitra K.; (2016). Segmentation of brain regions by integrating meta heuristic multilevel threshold with Markov random field. Current Medical Imaging Reviews, 12(1), pp.4–12.

2. Rashmi R.D.J.; Rajinikanth V.; Lin H.; Satapathy S.C.; In: Intelligent Data Engineering and Analytics Springer, Singapore.,663-670

3. Abirami D.; Shalini N.; Rajinikanth V.; Lin H.; Rao V.S.; In: Intelligent Data Engineering and Analytics (pp. 671-679). Springer, Singapore.

4. Dey N.; Rajinikanth V.; Lin H.; Shi F.; Applications of Bat Algorithm and its Variants Springer, Singapore.,45-60

5. Lin H.; Chaitra K.M.; Prabhu G.A.; Rajinikanth V.; (2019, March). Analyzing Dermoscopy Images using Soft-Computing Tools. n 2019 2nd International Conference on Signal Processing and Communication (ICSPC) (pp. 388-392). IEEE.