Page 10 - Handbook of Deep Learning in Biomedical Engineering Techniques and Applications

Preface xvii

to classify and detect the symptoms of plant disease with several
performance metrics. This chapter illustrates a comprehensive
review of deep learning models used to detect plant diseases, and
in some cases, the diseases have been identified before the
symptoms appear clearly.
Chapter 9 discusses about fundamentals of biomedical engi-
neering and deep learning. It also explores about applications of
deep learning in various problems of biomedical field.
Chapter 10 discusses the fundamentals of image processing
first, including segmentation and edge detection, followed by
identifying critical areas in biomedical images, denoising, and
applying image processing technique on various available
biomedical image datasets. The authors focus on tissue seg-
mentation, application of CNN in interpreting biomedical im-
ages, usage of different deep learning libraries for identifying
areas of interest in a biomedical image, computer-aided disease
diagnosis or prognosis, and so on. We will conclude by raising
research issues and suggesting future directions for further
improvements.
The aim of this book is to support the computational studies
at the research and postgraduation level with open problem-
solving techniques. We are confident that it will bridge the gap
for them by supporting novel solution in their problem solving.
At the end, editors have taken utmost care while finalizing the
chapters to the book, but we are open to receive your
constructive feedback, which will enable us to carry out neces-
sary points in our forthcoming books.

Valentina Emilia Balas

Brojo Kishore Mishra

Raghvendra Kumar