Blood cancer cell classification based on geometric mean transform and dissimilarity metrics

Seyed Mostafa Mousavi Kahaki, Md. Jan Nordin, Waidah Ismail, Sophia Jamila Zahra, Rosline Hassan

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Blood cancer is an umbrella term for cancers that affect the blood, bone marrow and lymphatic system. There are three main groups of blood cancer: leukemia, lymphoma and myeloma. Some types are more common than others. In this paper, a new image transform based on geometric mean properties of integral values in both horizontal and vertical image directions is proposed for leukemia cancer cell classification. Available classification methods using the classical feature extraction methods which are sensitive to rotation and deformation of the blood cells. The new transform is based on geometric mean projection, which -unlike other image transforms, such as Radon transform- is not considered all signals in an image with the same signal acquisition rate. Instead, it is general and thus applicable to all capturing signal functions to achieve sufficient invariant features. The geometric mean projection transforms (GMPT) guarantees that the detector only extracts the highly informative information from the object to achieve an invariant feature vector for an accurate classification process. This method has been used as cancer cell identification using microscopic Imagery analysis in this study. Dissimilarity metric calculation and shape analysis by using image transform has been used to extract the feature vectors of the imagery. Then, the accumulated feature vectors have been classified to different classes by using artificial neural network (ANN). The proposed technique has been evaluated in the standard images sourced from USIM, Malaysia. The evaluation results indicate the robustness of the technique in different types of images available in the dataset.

Original languageEnglish
Pages (from-to)223-234
Number of pages12
JournalPertanika Journal of Science and Technology
Volume25
Issue numberS6
Publication statusPublished - 1 Jun 2017

Fingerprint

blood cells
cancer
Blood Cells
Blood
transform
blood
Cells
Imagery (Psychotherapy)
Neoplasms
Radon
leukemia
neoplasms
Blood Group Antigens
Leukemia
Feature extraction
lymphatic system
Bone
radon
Lymphatic System
methodology

Keywords

  • Cancer cell classification image transform
  • Image processing
  • Pattern recognition

ASJC Scopus subject areas

  • Computer Science(all)
  • Chemical Engineering(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)

Cite this

Blood cancer cell classification based on geometric mean transform and dissimilarity metrics. / Kahaki, Seyed Mostafa Mousavi; Nordin, Md. Jan; Ismail, Waidah; Zahra, Sophia Jamila; Hassan, Rosline.

In: Pertanika Journal of Science and Technology, Vol. 25, No. S6, 01.06.2017, p. 223-234.

Research output: Contribution to journalArticle

Kahaki, Seyed Mostafa Mousavi ; Nordin, Md. Jan ; Ismail, Waidah ; Zahra, Sophia Jamila ; Hassan, Rosline. / Blood cancer cell classification based on geometric mean transform and dissimilarity metrics. In: Pertanika Journal of Science and Technology. 2017 ; Vol. 25, No. S6. pp. 223-234.
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