Hardware Segmentation on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis Using Xilinx System Generator

ElDahshan, Kamal A.; Masameer, Emad; Youssef, Mohamed S.; Mustafa, Mohammed Ahmed

doi:10.14569/ijacsa.2014.050906

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…Application specific devices are used for unsupervised analysis of medical data and medical diagnosis [12,13]. The devices to be used in such purposes, efficiently and with a short time to market are FPGAs [14] and graphis processing unis (GPUs) [15].…”

Section: Algorithms For Automated Microarray Image Processingmentioning

confidence: 99%

FSL-based Hardware Implementation for Parallel Computation of cDNA Microarray Image Segmentation

Bot¹,

Emerich²,

Martoiu³

et al. 2015

ijacsa

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Abstract-The present paper proposes a FPGA based hardware implementations for microarray image processing algorithms in order eliminate the shortcomings of the existing software platforms: user intervention, increased computation time and cost. The proposed image processing algorithms exclude user intervention from processing. An application-specific architecture is designed aiming microarray image processing algorithms parallelization in order to speed up computation. Hardware architectures for logarithm based image enhancement, profile computation and image segmentation are described. The methodology to integrate the hardware architecture within a microprocessor system is detailed. The Fast Simplex Link (FSL) bus is used to connect the hardware architecture as speed up coprocessor of the microarray image processing system. Timing considerations were presented considering the levels of parallelism that can be achieved by using our proposed hardware architectures. The FPGA technology was chosen for implementation, due to its parallel computation capabilities and ease of reconfiguration.

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Section: Algorithms For Automated Microarray Image Processingmentioning

confidence: 99%

FSL-based Hardware Implementation for Parallel Computation of cDNA Microarray Image Segmentation

Bot¹,

Emerich²,

Martoiu³

et al. 2015

ijacsa

View full text Add to dashboard Cite

show abstract

An Efficient Implementation of Acute Lymphoblastic Leukemia Images segmentation on the FPGA

ElDahshan

Youssef

Masameer

et al. 2015

AIVP

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In the medical field, image segmentation process is considered the most essential step in image analysis. In this work, the color segmentation for acute lymphoblastic leukemia images (ALL) is applied to segment each leukemia image into two clearly defined regions: blasts and background. The ALL segmentation process is based on hue channel (H) of HSV color space as a method in segmentation of WBC from its complicated background. This work presents an efficient framework for segmentation of ALL images on a reconfigurable logic platform using Simulink, MATLAB and Xilinx System Generator (XSG). This segmentation framework is implemented on a FPGA using basic Xilinx Blockset to minimize hardware resources and lower execution time to be suitable enough for medical applications. It is designed using XSG as DSP design tool that enables the use of Simulink models, implemented in VHDL and synthesized for three different Xilinx FPGA boards.

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Determination of optimum harvest time and physical and chemical quality properties of Shalakh (Aprikoz) apricot cultivar during fruit ripening

Tan

Kuş

Tan

et al. 2023

asphc

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Shalakh (Aprikoz), the most common table apricot cultivar grown in Iğdır province of Turkey, is known for its delicious taste, large volume, high water content, and short shelf life. This study aimed to determine optimal harvest time of cv. Shalakh apricot by measuring some significant physical and chemical parameters. Fruits were collected periodically at interval of 7 day during the study period. Weight, length, width, thickness, sphericity, color, color indices, soluble solids content, pH, firmness, elasticity, phenolic content (gallic acid and catechin) and organic acids (citric acid and ascorbic acid) were evaluated. Weight, length, width, thickness and sphericity traits increased gradually and reached the highest levels at 10th week after the full bloom. Color parameters (L*, a*, b*, C*, h° and ΔE), hardness, elasticity and organic acids indicated the optimal harvest time of cv. Shalakh of 10th week after the full bloom. Unlike previous studies, SSC and pH didn’t show clear information for harvest time.

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Hardware Segmentation on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis Using Xilinx System Generator

Cited by 3 publications

References 14 publications

FSL-based Hardware Implementation for Parallel Computation of cDNA Microarray Image Segmentation

FSL-based Hardware Implementation for Parallel Computation of cDNA Microarray Image Segmentation

An Efficient Implementation of Acute Lymphoblastic Leukemia Images segmentation on the FPGA

Determination of optimum harvest time and physical and chemical quality properties of Shalakh (Aprikoz) apricot cultivar during fruit ripening

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