Wamiq Manzoor Ahmed

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PURPOSE A web-based application was developed to remotely view slide specimens and control all functions of a research-level light microscopy workstation, called AccessScope. Students and scientists with upper limb mobility and visual impairments are often unable to use a light microscope by themselves and must depend on others in its operation. METHOD(More)
High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting(More)
Disease outbreaks due to contaminated food are a major concern not only for the food-processing industry but also for the public at large. Techniques for automated detection and classification of microorganisms can be a great help in preventing outbreaks and maintaining the safety of the nation's food supply. Identification and classification of foodborne(More)
WAMIQ MANZOOR AHMED∗, MUHAMMAD NAEEM AYYAZ∗, BARTEK RAJWA†, FARRUKH KHAN‡, ARIF GHAFOOR∗ and J. PAUL ROBINSON†,§ ∗School of Electrical and Computer Engineering, Purdue University, 465 Northwestern Avenue, West Lafayette, IN 47907, USA ghafoor@ecn.purdue.edu †Bindley Bioscience Center, Purdue University, 1203 West State Street, West Lafayette, IN 47907, USA(More)
Extraction of quantitative information about spatio- temporal events happening in cells is the key to understanding biological processes. In this paper we present a finite state machine (FSM)-based model for specification and identification of spatio-temporal events at the single-cell level. Cells are modeled as objects with specific attributes such as(More)
multilayered architecture and spatiotemporal models for searching, retrieving, and analyzing highthroughput biological imaging data. The analysis is divided into lowand high-level processing. At the lower level, we address issues like segmentation, tracking, and object recognition, and at the high level, we use finite state machineand Petrinet-based models(More)
High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these data sets for knowledge discovery requires high performance computational resources, efficient storage, and automated tools for(More)