Computational Models-Based Detection of Peripheral Malarial Parasites in Blood Smears.
| Autor: | Alharbi AH; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia., Aravinda CV; NITTE Deemed to Be University, Mangalore, India., Shetty J; NITTE Deemed to Be University, Mangalore, India., Jabarulla MY; School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea., Sudeepa KB; NITTE Deemed to Be University, Mangalore, India., Singh SK; Department of Civil Engineering, Wollega University, Nekemte, Oromia, Ethiopia. |
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| Jazyk: | angličtina |
| Zdroj: | Contrast media & molecular imaging [Contrast Media Mol Imaging] 2022 Jun 08; Vol. 2022, pp. 9171343. Date of Electronic Publication: 2022 Jun 08 (Print Publication: 2022). |
| DOI: | 10.1155/2022/9171343 |
| Abstrakt: | The most common human parasite as per the medical experts is the malarial disease, which is caused by a protozoan parasite, and Plasmodium falciparum, a common parasite in humans. A microscopist with expertise in malaria diagnosis must conduct this complex procedure to identify the stages of infection. This epidemic is an ongoing disease in some parts of the world, which is commonly found. A Kaggle repository was used to upload the data collected from the NIH portal. The dataset contains 27558 samples, of which 13779 samples carry parasites and 13779 samples do not. This paper focuses on two of the most common deep transfer learning methods. Unlike other feature extractors, VGG-19's fine-tuning and pretraining made it an ideal feature extractor. Several image classification models, including VGG-19, have been pretrained on larger datasets. Additionally, deep learning strategies based on pretrained models are proposed for detecting malarial parasite cases in the early stages, in addition to an accuracy rating of 98.34 ∗ 0.51%. Competing Interests: The authors declare that they have no conflicts of interest. (Copyright © 2022 Amal H. Alharbi et al.) |
| Databáze: | MEDLINE |
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