Academic Journal
Subject Review: Diagnoses cancer diseases systems for most body's sections using image processing techniques
| العنوان: | Subject Review: Diagnoses cancer diseases systems for most body's sections using image processing techniques |
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| المؤلفون: | Dena Nadir George, Haitham Salman Chyad, Raniah Ali Mustafa |
| المصدر: | Global Journal of Engineering and Technology Advances, 6(3), 056-062, (2021-03-30) |
| بيانات النشر: | Zenodo |
| سنة النشر: | 2021 |
| المجموعة: | Zenodo |
| مصطلحات موضوعية: | Feed-Forward Back Propagation NN, A gray-level co-occurrence matrix (GLCM), Dense Scale Invariant Feature Transform (DSIFT), Deep convolutional neural network (DCNN) |
| الوصف: | Medical imaging has become an important part of diagnosing, early detection, and treating cancers. In this paper, a comprehensive survey on various image processing techniques for medical images specifically examined cancer diseases for most body sections. These sections are Bone, Liver, Kidney, Breast, Lung, and Brain. Detection of medical imaging involves different stages such as classification, segmentation, image pre-processing, and feature extraction. With regard to this work, many image processing methods will be studied, over 10 surveys reviewing classification, feature extraction, and segmentation methods utilized image processing for cancer diseases for most body's sections are clearly reviewed. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| Relation: | https://zenodo.org/communities/gjeta; https://doi.org/10.5281/zenodo.4643419; https://doi.org/10.5281/zenodo.4643420; oai:zenodo.org:4643420; https://doi.org/10.30574/gjeta.2021.6.3.0031 |
| DOI: | 10.5281/zenodo.4643420 |
| DOI: | 10.30574/gjeta.2021.6.3.0031 |
| الاتاحة: | https://doi.org/10.5281/zenodo.4643420 https://doi.org/10.30574/gjeta.2021.6.3.0031 |
| Rights: | info:eu-repo/semantics/openAccess ; Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcode |
| رقم الانضمام: | edsbas.80A8046B |
| قاعدة البيانات: | BASE |
| DOI: | 10.5281/zenodo.4643420 |
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