Deep Learning Features Restoration and Regional Longitudinal Fitting of Computed Tomography Images using Convolution Neural Network-Reference-Cited by-同舟云学术

Deep Learning Features Restoration and Regional Longitudinal Fitting of Computed Tomography Images using Convolution Neural Network

Published:2022-11-10 Issue: Volume: Page:
ISSN:
Container-title:2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)
language:
Short-container-title:

Author:

Krishnaswamy R¹,Titus Anita²,Gengalakshmi. G³,Srinivasan S.⁴,Manikandan J.⁵

Affiliation:

1. University College of Engineering,Department of Electronics and Communication Engineering,Ariyalur,Tamil Nadu,India

2. Jeppiaar Engineering College,Department of Electronics and Communication Engineering,Chennai,Tamil Nadu,India

3. Sri Sairam Homoeopathy Medical College and Research Center,Department of Human Anatomy,Chennai,Tamil Nadu,India

4. Saveetha University,Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences,Department of Biomedical Engineering,Chennai,Tamil Nadu,India

5. Hindusthan College of Engineering and Technology,Department of Mechanical Engineering,Coimbatore,Taminadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9986507/9986494/09987413.pdf?arnumber=9987413

Reference19 articles.

1. Underwater Object Recognition Using KNN Classifier

2. Imagenet classification with deep convolutional neural networks;krizhevsky;Advances in neural information processing systems,2012

3. Penalized Likelihood PET Image Reconstruction Using Patch-Based Edge-Preserving Regularization

4. Corrections for accidental coincidences and attenuation in maximum-likelihood image reconstruction for positron-emission tomography

5. Dynamic PET reconstruction using temporal patch-based low rank penalty for ROI-based brain kinetic analysis