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Deep Learning for Cancer Diagnosis

Overview of attention for book
Cover of 'Deep Learning for Cancer Diagnosis'

Table of Contents

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    Book Overview
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    Chapter 1 Fusion of Deep Learning and Image Processing Techniques for Breast Cancer Diagnosis
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    Chapter 2 Performance Evaluation of Classification Algorithms on Diagnosis of Breast Cancer and Skin Disease
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    Chapter 4 Classification of Canine Fibroma and Fibrosarcoma Histopathological Images Using Convolutional Neural Networks
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    Chapter 7 Improved Deep Learning Techniques for Better Cancer Diagnosis
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    Chapter 9 Effective Use of Deep Learning and Image Processing for Cancer Diagnosis
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    Chapter 11 Deep Learning for Brain Tumor Segmentation
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    Chapter 12 Convolutional Neural Network Approach for the Detection of Lung Cancers in Chest X-Ray Images
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    Chapter 14 Brain Tumor Segmentation Using 2D-UNET Convolutional Neural Network
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    Chapter 16 Deep Learning for Magnetic Resonance Images of Gliomas
Attention for Chapter 4: Classification of Canine Fibroma and Fibrosarcoma Histopathological Images Using Convolutional Neural Networks
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Citations

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2 Mendeley
Summary Dimensions citations
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Chapter title
Classification of Canine Fibroma and Fibrosarcoma Histopathological Images Using Convolutional Neural Networks
Chapter number 4
Book title
Deep Learning for Cancer Diagnosis
Published by
Springer, Singapore, September 2020
DOI 10.1007/978-981-15-6321-8_4
Book ISBNs
978-9-81-156320-1, 978-9-81-156321-8
Authors

İsmail Kırbaş, Özlem Özmen

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 50%
Unspecified 1 50%
Readers by discipline Count As %
Unspecified 1 50%
Medicine and Dentistry 1 50%

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