Leukemia Detection Using Invariant Structural Cascade Segmentation Based on Deep Vectorized Scaling Neural Network

AbstractLeukemia is one of the deadliest diseases that occur in white blood cells which is identified in microscopic images from blood samples. Researchers have developed various techniques to diagnose leukemia using a machine learning approach by analyzing micro imaging blood samples. During image screening, the Damaged cells be identified based on manually counting on similar structure lymphocytes and monocytes structures, but the variant difference of both cells aren’t identified accurately. So the identification failures that occur lead to failed accurate cancer detection because feature variants project equal cell structure. To resolve this problem, we propose an Invariant Structural Cascade Segmentation (ISCS) based on Deep Vectorized Scaling Neural Network (DVSNN) is implemented to detect the Leukemia Cancer automatically from bio-blood samples micro image for early diagnosis. First, the Leukemia Cancer micro-image dataset (LCMID) was collected and preprocessed into a noise-free dataset based on adaptive median filters. Then the segmentation was carried to partition the microcells using Invariant structural cascade segmentation (ISCS) optimized with watershed to identify the features such as texture, pixel color, pixel intensity. For identifying the structural components of cells variation difference using Angular Vector Projection (AVP) was applied to find the structural variance. Then the histogram color equalizer (HCE) was applied to select the damaged cells using K-counts and their feature weight. Then the selected feature weights are trained into Deep vectorized scaling the neural network to classify the risk of the Leukemia cancer cells. This identifies the cancer cells effectively from micro image cells for detecting the risk of the patients. This improves the sensitivity, specificity rate as well in classification accuracy compared to the other methods.Keywords: Adaptive median filtersAngular Vector Projection (AVP)Deep Vectorized Scaling Neural Network (DVSNN)histogram color equalizer (HCE)invariant structural cascade segmentation (ISCS)leukemiamicroscopic images Author ContributionsArthi A: Conceptualization, Methodology, Visualization, Investigation, Data Validation and Writing - Original draft preparation; Vennila V: Supervision and Data Curation; Arun Kumar U: Reviewing and Editing.Availability of Data and MaterialsData sharing not applicable to this article as no datasets were generated or analyzed during the current study.Competing InterestsThe authors declare that they do not have any competing interest. The authors of this research acknowledge that they are not involved in any financial interest.Consent for PublicationNot Applicable.DeclarationsThe authors certify that this material or similar material has not been and will not be submitted to or published in any other publication before. Furthermore, the authors certify that they have participated sufficiently in the work to take public responsibility for the content, including participation in the concept, design, analysis, writing, or revision of the manuscript.Ethics Approval and Consent to ParticipateNot Applicable.