Computer Vision and Machine Intelligence in Medical Image Analysis : International Symposium, ISCMM 2019 / edited by Mousumi Gupta, Debanjan Konar, Siddhartha Bhattacharyya, Sambhunath Biswas
Chapter 1. A Novel Method for Pneumonia Diagnosis from Chest X-Ray Images Using Deep Residual Learning with Separable Convolutional Networks -- Chapter 2. Identification of Neural Correlates of Face Recognition Using Machine Learning Approach -- Chapter 3. An Overview of Remote Photoplethysmography Methods for Vital Sign Monitoring -- Chapter 4. Fuzzy Inference System for Efficient Lung Cancer Detection -- Chapter 5. Medical Image Compression Scheme Using Number Theoretic Transform -- Chapter 6. The Retinal Blood Vessel Segmentation Using Expected Maximization Algorithm -- Chapter 7. Classification Algorithms to Predict Heart Diseases-A Survey -- Chapter 8. A Hybrid Filtering Based Retinal Blood Vessel Segmentation Algorithm -- Chapter 9. Laser Scar Classification in Retinal Fundus Images Using Wavelet Transform and Local Variance -- Chapter 10. Automated Segmentation of Cervical Cells Using MSER Algorithm and Gradient Embedded Cost Function Based Level Set Method -- Chapter 11. Macroscopic Reconstruction for Histopathology Images A Survey -- Chapter 12. Likelihood Prediction of Diabetes at Early Stage Using Data Mining Techniques -- Chapter 13. Medical Diagnosis Under Uncertain Environment Through Bipolar-valued Fuzzy Sets -- Chapter 14. Design and Analysis of Novel Room Temperature T-Ray Source for Biomedical Imaging: Application in Full Body Prosthetics.
This book includes high-quality papers presented at the Symposium 2019, organised by Sikkim Manipal Institute of Technology (SMIT), in Sikkim from 26–27 February 2019. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.
| Medienart: |
E-Book |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
Singapore: Springer ; 2020 |
| Ausgabe: |
1st ed. 2020 |
| Reihe: |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Gupta, Mousumi [HerausgeberIn] |
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| Links: |
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| ISBN: |
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| Themen: |
Biomedical engineering |
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| Umfang: |
1 Online-Ressource (XII, 150 p. 62 illus., 31 illus. in color) |
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| doi: |
10.1007/978-981-13-8798-2 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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1676313109 |
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| 520 | |a This book includes high-quality papers presented at the Symposium 2019, organised by Sikkim Manipal Institute of Technology (SMIT), in Sikkim from 26–27 February 2019. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals | ||
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