research-article

Images in Space and Time: Real Big Data in Healthcare

Author:

Eman BadrAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 54, Issue 6

Article No.: 113, Pages 1 - 38

https://doi.org/10.1145/3453657

Published: 13 July 2021 Publication History

Abstract

Medical imaging diagnosis is mostly subjective, as it depends on medical experts. Hence, the service provided is limited by expert opinion variations and image complexity as well. However, with the increasing advancements in deep learning field, techniques are developed to help in the diagnosis and risk assessment processes. In this article, we survey different types of images in healthcare. A review of the concept and research methodology of Radiomics will highlight the potentials of integrated diagnostics. Convolutional neural networks can play an important role in next generations of automated imaging biomarker extraction and big data analytics systems. Examples are provided of what is already feasible today and also describe additional technological components required for successful clinical implementation.

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ACM Computing Surveys Volume 54, Issue 6

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July 2022

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EISSN:1557-7341

DOI:10.1145/3475936

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Published in CSUR Volume 54, Issue 6

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F. Khalifa ABadr E(2023)Deep Learning for Image Segmentation: A Focus on Medical ImagingComputers, Materials & Continua10.32604/cmc.2023.03588875:1(1995-2024)Online publication date: 2023
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Sethy PSachdeva SKumar S(2023)Implementation And Performance Comparison of CNN-Based Semantic Segmentation Methods for Biomedical Application2023 Second International Conference on Informatics (ICI)10.1109/ICI60088.2023.10421208(1-5)Online publication date: 23-Nov-2023
https://doi.org/10.1109/ICI60088.2023.10421208
Rahman AHasan KKundu DIslam MDebnath TBand SKumar N(2023)On the ICN-IoT with federated learning integration of communicationFuture Generation Computer Systems10.1016/j.future.2022.08.004138:C(61-88)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.future.2022.08.004
Jaszcz APołap DDamaševičius R(2022)Lung X-Ray Image Segmentation Using Heuristic Red Fox Optimization AlgorithmScientific Programming10.1155/2022/44941392022Online publication date: 1-Jan-2022
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Dashora RBabu M(2022)A Survey on Advancements of Real-Time Analytics Architecture ComponentsComputational Methods and Data Engineering10.1007/978-981-19-3015-7_41(547-559)Online publication date: 9-Sep-2022
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Rundo LMilitello CConti VZaccagna FHan C(2021)Advanced Computational Methods for Oncological Image AnalysisJournal of Imaging10.3390/jimaging71102377:11(237)Online publication date: 12-Nov-2021
https://doi.org/10.3390/jimaging7110237
Militello CRanieri ARundo LD’Angelo IMarinozzi FBartolotta TBini FRusso G(2021)On Unsupervised Methods for Medical Image Segmentation: Investigating Classic Approaches in Breast Cancer DCE-MRIApplied Sciences10.3390/app1201016212:1(162)Online publication date: 24-Dec-2021
https://doi.org/10.3390/app12010162

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