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Classification of COVID-19 in CT Scans using Multi-Source Transfer Learning [article]

Alejandro R. Martinez
2020 arXiv   pre-print
In this study, we propose the use of Multi-Source Transfer Learning (MSTL) to improve upon traditional Transfer Learning for the classification of COVID-19 from CT scans.  ...  Due to an inherent lack of available COVID-19 CT data, these research efforts have been forced to leverage the use of Transfer Learning.  ...  ACKNOWLEDGEMENTS This work was initiated and facilitated by CS 89.20/189 -Data Science for Health (Spring 2020) at Dartmouth College, taught by Professor Temiloluwa Prioleau.  ... 
arXiv:2009.10474v1 fatcat:ugwqgvpw3vh6rhsw73a7t5qo2e

Soft Attention Based DenseNet Model for Parkinson's Disease Classification Using SPECT Images

Mahima Thakur, Harisudha Kuresan, Samiappan Dhanalakshmi, Khin Wee Lai, Xiang Wu
2022 Frontiers in Aging Neuroscience  
For visually analyzing the region of interest (ROI) from the images after classification, Soft Attention Maps and feature map representation are used.OutcomesThe model obtains an overall accuracy of 99.2%  ...  The most effective imaging modality for detecting the condition is DaTscan, a variety of single-photon emission computerized tomography (SPECT) imaging method.  ...  ACKNOWLEDGMENTS We would like to thank the SRM Institute of Science and Technology, the University of Malaya and Xuzhou Medical University Xuzhou for supporting this research.  ... 
doi:10.3389/fnagi.2022.908143 pmid:35912076 pmcid:PMC9326232 fatcat:l2w32kvho5evzdxvhevr7uaysm

Utilizing Knowledge Distillation in Deep Learning for Classification of Chest X-ray Abnormalities

Thi Kieu Khanh Ho, Jeonghwan Gwak
2020 IEEE Access  
In Table I , results are shown for the six pre-trained deep models used for normal transfer learning (referred to as base training).  ...  gradients to better understand our deep learning model's decisionmaking process.  ... 
doi:10.1109/access.2020.3020802 fatcat:ucyyrx3ijzft3he2kabn7tgqyi

From Shallow to Deep: Compositional Reasoning over Graphs for Visual Question Answering [article]

Zihao Zhu
2022 arXiv   pre-print
It is effortless for human but challenging for machines.  ...  In order to achieve a general visual question answering (VQA) system, it is essential to learn to answer deeper questions that require compositional reasoning on the image and external knowledge.  ...  However, deeper questions commonly cover relationships (e.g. geometric positions or semantic interactions between objects) beyond mere object detection, so we propose the Relate module to transfer node  ... 
arXiv:2206.12533v1 fatcat:4ipke63dwfcazl4prpl73gd7si

Detection of Early Pneumonia on Individual CT Scans with Dilated Convolutions

Iurii Krak, Olexander Barmak, Pavlo Radiuk
2021 International Workshop on Intelligent Information Technologies & Systems of Information Security  
Thus, early diagnosis and detection of this lung disease are crucial in successful treatment and constant monitoring.  ...  An effective dilated convolution operation with different rates, combining features of various receptive fields, was utilized to detect and analyze visual deviations in targeted images.  ...  For example, the study [6] applied a transfer training method to a 36-layer CNN to effectively classify pneumonia on a small dataset and used gradient-based CAMs to interpret the automated diagnosis  ... 
dblp:conf/intelitsis/KrakBR21 fatcat:zggrsr56tbe5xekpmqc4eb6xbu

Augmenting Sensor Performance with Machine Learning Towards Smart Wearable Sensing Electronic Systems

Songlin Zhang, Lakshmi Suresh, Jiachen Yang, Xueping Zhang, Swee Ching Tan
2022 Advanced Intelligent Systems  
, carefully designed soft circuits, etc.  ...  As an important subset of AI, Machine learning (ML) has already been widely implemented in many fields of  ...  is processed in the fusing algorithm (bottom); h) best accuracy was achieved via bioinspired somatosensory-visual (BSV) associated learning algorithm.  ... 
doi:10.1002/aisy.202100194 fatcat:7ai5exgvsvgb3kro2brldreqpe

Knee Injury Detection Using Deep Learning on MRI Studies: A Systematic Review

Athanasios Siouras, Serafeim Moustakidis, Archontis Giannakidis, Georgios Chalatsis, Ioannis Liampas, Marianna Vlychou, Michael Hantes, Sotiris Tasoulis, Dimitrios Tsaopoulos
2022 Diagnostics  
There are several possible avenues of further exploration of deep learning for improving MRI-based knee injury diagnosis.  ...  In recent years, deep-learning-based approaches have monopolized knee injury detection in MRI studies.  ...  Deep Learning with Transfer Learning Bien et al.  ... 
doi:10.3390/diagnostics12020537 pmid:35204625 pmcid:PMC8871256 fatcat:xp7vdedh35exjhakh7qvdzorie

Point-of-Care Diabetic Retinopathy Diagnosis: A Standalone Mobile Application Approach [article]

Misgina Tsighe Hagos
2020 arXiv   pre-print
This approach could be transferred to other areas of medical image classification.  ...  Traditional diagnosis of diabetic retinopathy requires trained ophthalmologists and expensive imaging equipment to reach healthcare centres in order to provide facilities for treatment of preventable blindness  ...  The axons of the ganglion cells found in the third layer convey the visual information as encoded by the retina to the next synapse point in the visual pathway via the optic nerve.  ... 
arXiv:2002.04066v1 fatcat:evsa2qfaebcy5jfjgcespdbhoi

ECOVNet: An Ensemble of Deep Convolutional Neural Networks Based on EfficientNet to Detect COVID-19 From Chest X-rays [article]

Nihad Karim Chowdhury, Muhammad Ashad Kabir, Md. Muhtadir Rahman, Noortaz Rezoana
2020 arXiv   pre-print
At first, the open-access large chest X-ray collection is augmented, and then ImageNet pre-trained weights for EfficientNet is transferred with some customized fine-tuning top layers that are trained,  ...  This paper proposed an ensemble of deep convolutional neural networks (CNN) based on EfficientNet, named ECOVNet, to detect COVID-19 using a large chest X-ray data set.  ...  On the other hand, diagnosis based on chest X-ray appears to be a propitious solution for COVID-19 detection and treatment.  ... 
arXiv:2009.11850v2 fatcat:w7xkuzap55hxdomqjbit6udfxu

Guest Editorial: Data-Driven Management of Complex Systems Through Plant-Wide Performance Supervision

Okyay Kaynak, Steven Ding, Ahmet Palazoglu, Hao Luo
2021 IEEE Transactions on Industrial Informatics  
The authors have constructed the multilevel monitoring indexes and fault contribution indexes for the visualization of the fault detection and diagnosis [item 2) in the Appendix].  ...  To achieve quality-related root cause diagnosis for nonlinear processes, in "Quality-related root cause diagnosis based on orthogonal kernel principal component regression and transfer entropy [item 5)  ... 
doi:10.1109/tii.2020.3023259 fatcat:2x44ydldbreqdcyejz5jui7q24

Region Space Guided Transfer Function Design for Nonlinear Neural Network Augmented Image Visualization

Fei Yang, Xiangxu Meng, JiYing Lang, Weigang Lu, Lei Liu
2018 Advances in Multimedia  
There is a strong need today for the acquisition of high quality visualization result for various fields, such as biomedical or other scientific field.  ...  The noise in the volume data is suppressed effectively and the boundary between materials can be differentiated clearly by the transfer function designed via the modified 2D histogram.  ...  The gradient [21, 22] and curve [23, 24] are introduced as the second variable for the twodimensional transfer function. Roettger et al.  ... 
doi:10.1155/2018/7479316 fatcat:gdetgxn7zbhufb3lzujkmjunmq

Risk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning [chapter]

Sarfaraz Hussein, Kunlin Cao, Qi Song, Ulas Bagci
2017 Lecture Notes in Computer Science  
In order to address the need for a large amount for training data for CNN, we resort to transfer learning to obtain highly discriminative features.  ...  Moreover, we also acquire the task dependent feature representation for six high-level nodule attributes and fuse this complementary information via a Multi-task learning (MTL) framework.  ...  Although CT imaging remains the gold standard for lung cancer detection and diagnosis, Computer-Aided Diagnosis (CAD) and quantification tools are often necessary.  ... 
doi:10.1007/978-3-319-59050-9_20 fatcat:oq23wasdgrggpevudeg5c5a3ei

Front Matter: Volume 10574

Proceedings of SPIE, Elsa D. Angelini, Bennett A. Landman
2018 Medical Imaging 2018: Image Processing  
Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model.  ...  soft distance constraint for dual surfaces segmentation in medical images Topological leakage detection and freeze-and-grow propagation for improved CT-based airway segmentation Student beats the teacher  ...  Circle-like foreign element detection in chest x-rays using normalized cross-correlation and unsupervised clustering [10574-66] 10574 1W Orientation regression in hand radiographs: a transfer learning  ... 
doi:10.1117/12.2315755 fatcat:jdfbaent6vhu5dwlrqrqt66vce

Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review [article]

Mahdi Rezaei, Mahsa Shahidi
2020 arXiv   pre-print
This is an ever-growing research for the cases where we have very limited or no datasets available and at the same time, the detection/recognition system has human-like characteristics in learning new  ...  Therefore, it makes it applicable in real-world scenarios, from developing autonomous vehicles to medical imaging and COVID-19 Chest X-Ray (CXR) based diagnosis.  ...  Using soft-OR, the attributes are divided into groups, and the label class from unseen samples is predicted via a soft-AND within these groups.  ... 
arXiv:2004.14143v2 fatcat:erh6xyog7bb5vofcebkk2zxumm

SSD-KD: A Self-supervised Diverse Knowledge Distillation Method for Lightweight Skin Lesion Classification Using Dermoscopic Images [article]

Yongwei Wang, Yuheng Wang, Tim K. Lee, Chunyan Miao, Z. Jane Wang
2022 arXiv   pre-print
However, most studies in skin cancer detection keep pursuing high prediction accuracies without considering the limitation of computing resources on portable devices.  ...  Over the last few years, computer-aided diagnosis has been rapidly developed and make great progress in healthcare and medical practices due to the advances in artificial intelligence.  ...  Knowledge Distillation (KD), proposed as an extended model compression method, can transfer the learned knowledge from a complicated model (the teacher) to a simple model (the student) by sharing the soft  ... 
arXiv:2203.11490v2 fatcat:lpxi4cku45atbcy62dxwggsv5a
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