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  • [Publikasi] Morphological, Texture, and Color Feature Analysis for Erythrocyte Classification in Thalassemia Cases

[Publikasi] Morphological, Texture, and Color Feature Analysis for Erythrocyte Classification in Thalassemia Cases

  • Publikasi
  • 19 August 2020, 08.24
  • Oleh: sonia.yunita
  • 0

Selamat kepada Dyah Aruming Tyas (Mahasiswa PMDSU Ilmu Komputer), Prof. Sri Hartati, Ph.D, Bapak Agus Harjoko, Ph.D. dan Dr. dr. Tri Ratnaningsih yang telah mempublikasikan paper berjudul “Morphological, Texture, and Color Feature Analysis for Erythrocyte Classification in Thalassemia Cases”. Paper dipublikasikan pada international journal IEEEAccess (Scopus Q1, Impact Factor : 3,74)

Abstract:

Abnormal erythrocytes have diverse shapes. The appearance of specific erythrocyte shapes in a person’s blood can indicate certain diseases, including thalassemia. We used thalassemia peripheral blood smear images and applied a segmentation process to produce single erythrocyte sub-images. Each erythrocyte has a unique shape. The selection of appropriate features to represent erythrocytes is critical for classification accuracy. We used morphological features such as moment invariants, geometry parameters of the cell and central pallor, and distance angle signature (DAS) morphological features of the cell and central pallor. We combined morphological features with texture and color features to increase the accuracy of erythrocyte classification. In this study, the multi-layer perceptron is used to classify nine shapes of erythrocytes present in thalassemia cases. The experimental results of 7108 erythrocytes indicated an accuracy of 98.11% based on the combination of features. The experimental results also show that the combination of features we proposed produced higher classification accuracy than previous work, which yielded an accuracy of 93.77%.
Keywords: Classification, distance angle signature, erythrocytes, morphological feature, thalassemia
Artikel lengkap dapat diakses melalui URL
https://ieeexplore.ieee.org/document/9046795

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Universitas Gadjah Mada

Laboratorium Sistem Cerdas
Departemen Ilmu Komputer dan Elektronika
Fakultas Matematika dan Ilmu Pengetahuan Alam
Universitas Gadjah Mada

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