Current Applications of Deep Learning in Cancer Diagnostics  book cover
1st Edition

Current Applications of Deep Learning in Cancer Diagnostics

  • Available for pre-order. Item will ship after February 22, 2023
ISBN 9781032233857
February 22, 2023 Forthcoming by CRC Press
200 Pages 27 Color & 52 B/W Illustrations

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Book Description

This book examines deep learning-based approaches in the field of cancer diagnostics, as well as pre-processing techniques which are essential to cancer diagnostics. Topics include: introduction to current applications of deep learning in cancer diagnostics; pre-processing of cancer data using deep learning; review of deep learning techniques in oncology; overview of advanced deep learning techniques in cancer diagnostics; prediction of cancer susceptibility using deep learning techniques; prediction of cancer reoccurrence using deep learning techniques; deep learning techniques to predict the grading of human cancer; different human cancer detection using deep learning techniques; prediction of cancer survival using deep learning techniques; complexity in the use of deep learning in cancer diagnostics; challenges and future scopes of deep learning techniques in oncology.

Table of Contents

  1. Contemporary Trends in the Early Detection and Diagnosis of Human Cancers using Deep Learning Techniques 
  2. Nirmala Vasan Balasenthilkumaran and Sumit Kumar Jindal.


  3. Cancer Data Pre-Processing Techniques 
  4. Jyotismita Chaki. 


  5. A Survey on Deep Learning Techniques for Breast, Leukemia and Cervical Cancer Prediction 
  6. N Jothiaruna and Anny Leema A.


  7. An Optimized Deep Learning Technique for Detecting Lung Cancer from CT Images 
  8. Vanitha. M, Mangayarkarasi. R, Angulakshmi. M, and Deepa. M.


  9. Brain Tumor Segmentation Utilizing MRI Multimodal Images with Deep Learning 
  10. Chellaswamy C, Geetha T S, Markkandan S, and Thiruvalar Selvan.

  11. Detection and Classification of Brain Tumors using Light Weight Convolutional Neural Network 
  12. Sabyasachi Mukherjee, Oishila Bandyopadhyay, and Arindam Biswas.

  13. Parallel Dense Skip Connected CNN Approach for Brain Tumor Classification 
  14. G. Yogeswararao, V. Naresh, R. Malmathanraj, P. Palanisamy, and Karthik Balasubramanian.

  15. Liver Tumor Segmentation Using Deep Learning Neural Networks 
  16. Sumedha Vadlamani, Charit Gupta Paluri, Jaydev Jangiti, Sumit Kumar Jindal.


  17. Deep Learning Algorithms for Classification and Prediction of Acute Lymphoblastic Leukemia 
  18. Amrita I and Snigdha Sen.

  19. Cervical Pap smear Screening and Cancer Detection using Deep Neural Network
  20. Munakala Lohith, Soumi Bardhan, and Oishila Bandyopadhya.

  21. Cancer detection using deep neural network: Differentiation of Squamous Carcinoma cells in Oral Pathology 
  22. Jayanthi Ganapathy.

  23. Challenges and Future scopes in Current Applications of Deep Learning in Human Cancer Diagnostics 
    1. C.S. Vidhya, M. Loganathan, and R. Meenatchi.

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Dr. Jyotismita Chaki is an Assistant Professor at School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.

Dr. Aysegul Ucar is a Professor in Department of Mechatronics Engineering, Firat University, Turkey.