Circle Detection Using a Gabor Annulus

Rhodes, Adam; Bai, Libing

doi:10.5244/c.25.108

Cited by 10 publications

(5 citation statements)

References 26 publications

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“…The Gabor annulus method, based on the advantageous properties of Gabor wavelet filters, is a popular method for recognizing patterns. 46 This filter is convolved across the image, resulting in a large response in areas where an image’s features or patterns match their specific scale, orientation, and location. In other words, the filters are fine-tuned to recognize beads, and the alignment of the beads and the Gabor annulus filter results in a large response at the beads’ centroids.…”

Section: Resultsmentioning

confidence: 99%

Programmable bio-nano-chip system: a flexible point-of-care platform for bioscience and clinical measurements

et al. 2015

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The development of integrated instrumentation for universal bioassay systems serves as a key goal for the lab-on-a-chip community. The programmable bio-nano-chip (p-BNC) system is a versatile multiplexed and multiclass chemical- and bio-sensing system for bioscience and clinical measurements. The system is comprised of two main components, a disposable cartridge and a portable analyzer. The customizable single-use plastic cartridges, which now can be manufactured in high volumes using injection molding, are designed for analytical performance, ease of use, reproducibility, and low cost. These labcard devices implement high surface area nano-structured biomarker capture elements that enable high performance signaling and are index matched to real-world biological specimens. This detection modality, along with the convenience of on-chip fluid storage in blisters and self-contained waste, represents a standard process to digitize biological signatures at the point-of-care. A companion portable analyzer prototype has been developed to integrate fluid motivation, optical detection, and automated data analysis, and it serves as the human interface for complete assay automation. In this report, we provide a systems-level perspective of the p-BNC universal biosensing platform with an emphasis on flow control, device integration, and automation. To demonstrate the flexibility of the p-BNC, we distinguish diseased and non-case patients across three significant disease applications: prostate cancer, ovarian cancer, and acute myocardial infarction. Progress towards developing a rapid 7 minute myoglobin assay is presented using the fully automated p-BNC system.

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Section: Resultsmentioning

confidence: 99%

Programmable bio-nano-chip system: a flexible point-of-care platform for bioscience and clinical measurements

et al. 2015

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“…First, the finite difference image identifies the bead's outer edge. Next, beads within the expected size distribution are identified via generating several Gabor annuli 24 with slightly different properties and subsequently performing 2-D convolution operations on the derivative image. The resulting convolution responses are normalized and averaged, and the bead locations are defined by the maximum averaged response.…”

Section: Accounts Of Chemical Researchmentioning

confidence: 99%

Programmable Bio-nanochip Platform: A Point-of-Care Biosensor System with the Capacity To Learn

et al. 2016

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The combination of point-of-care (POC) medical microdevices and machine learning has the potential transform the practice of medicine. In this area, scalable lab-on-a-chip (LOC) devices have many advantages over standard laboratory methods, including faster analysis, reduced cost, lower power consumption, and higher levels of integration and automation. Despite significant advances in LOC technologies over the years, several remaining obstacles are preventing clinical implementation and market penetration of these novel medical microdevices. Similarly, while machine learning has seen explosive growth in recent years and promises to shift the practice of medicine toward data-intensive and evidence-based decision making, its uptake has been hindered due to the lack of integration between clinical measurements and disease determinations. In this Account, we describe recent developments in the programmable bio-nanochip (p-BNC) system, a biosensor platform with the capacity for learning. The p-BNC is a "platform to digitize biology" in which small quantities of patient sample generate immunofluorescent signal on agarose bead sensors that is optically extracted and converted to antigen concentrations. The platform comprises disposable microfluidic cartridges, a portable analyzer, automated data analysis software, and intuitive mobile health interfaces. The single-use cartridges are fully integrated, self-contained microfluidic devices containing aqueous buffers conveniently embedded for POC use. A novel fluid delivery method was developed to provide accurate and repeatable flow rates via actuation of the cartridge's blister packs. A portable analyzer instrument was designed to integrate fluid delivery, optical detection, image analysis, and user interface, representing a universal system for acquiring, processing, and managing clinical data while overcoming many of the challenges facing the widespread clinical adoption of LOC technologies. We demonstrate the p-BNC's flexibility through the completion of multiplex assays within the single-use disposable cartridges for three clinical applications: prostate cancer, ovarian cancer, and acute myocardial infarction. Toward the goal of creating "sensors that learn", we have developed and describe here the Cardiac ScoreCard, a clinical decision support system for a spectrum of cardiovascular disease. The Cardiac ScoreCard approach comprises a comprehensive biomarker panel and risk factor information in a predictive model capable of assessing early risk and late-stage disease progression for heart attack and heart failure patients. These marker-driven tests have the potential to radically reduce costs, decrease wait times, and introduce new options for patients needing regular health monitoring. Further, these efforts demonstrate the clinical utility of fusing data from information-rich biomarkers and the Internet of Things (IoT) using predictive analytics to generate single-index assessments for wellness/illness status. By promoting disease prevention and personalized wellness...

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“…Rhodes and Bai [ 12 ] presented a circle detection method using specific properties of Gabor wavelet filter to detect the image features such as circularity. It is able to extract radius wraps around the origin and the plane wave radiates from the center of the filter.…”

Section: Related Workmentioning

confidence: 99%

Automatic Detection and Quantification of WBCs and RBCs Using Iterative Structured Circle Detection Algorithm

Alomari

Abdullah

Azma

et al. 2014

Computational and Mathematical Methods in Medicine

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Segmentation and counting of blood cells are considered as an important step that helps to extract features to diagnose some specific diseases like malaria or leukemia. The manual counting of white blood cells (WBCs) and red blood cells (RBCs) in microscopic images is an extremely tedious, time consuming, and inaccurate process. Automatic analysis will allow hematologist experts to perform faster and more accurately. The proposed method uses an iterative structured circle detection algorithm for the segmentation and counting of WBCs and RBCs. The separation of WBCs from RBCs was achieved by thresholding, and specific preprocessing steps were developed for each cell type. Counting was performed for each image using the proposed method based on modified circle detection, which automatically counted the cells. Several modifications were made to the basic (RCD) algorithm to solve the initialization problem, detecting irregular circles (cells), selecting the optimal circle from the candidate circles, determining the number of iterations in a fully dynamic way to enhance algorithm detection, and running time. The validation method used to determine segmentation accuracy was a quantitative analysis that included Precision, Recall, and F-measurement tests. The average accuracy of the proposed method was 95.3% for RBCs and 98.4% for WBCs.

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Circle Detection Using a Gabor Annulus

Cited by 10 publications

References 26 publications

Programmable bio-nano-chip system: a flexible point-of-care platform for bioscience and clinical measurements

Programmable bio-nano-chip system: a flexible point-of-care platform for bioscience and clinical measurements

Programmable Bio-nanochip Platform: A Point-of-Care Biosensor System with the Capacity To Learn

Automatic Detection and Quantification of WBCs and RBCs Using Iterative Structured Circle Detection Algorithm

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