Prof. Golshah A. Naghdy Profile

Prof. Golshah A. Naghdy

at Univ of Wollongong

SPIE Involvement:

Author

Publications (11)

Proceedings Article | 15 October 2012 Paper

Computer aided decision support system for cervical cancer classification

Rahmadwati Rahmadwati, Golshah Naghdy, Montserrat Ros, Catherine Todd

Proceedings Volume 8499, 849919 (2012) https://doi.org/10.1117/12.931284

KEYWORDS: Image segmentation, Wavelets, Image processing, Cervical cancer, Feature extraction, Image classification, Cancer, Biopsy, Diagnostics, Image filtering

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Conventional analysis of a cervical histology image, such a pap smear or a biopsy sample, is performed by an expert pathologist manually. This involves inspecting the sample for cellular level abnormalities and determining the spread of the abnormalities. Cancer is graded based on the spread of the abnormal cells. This is a tedious, subjective and time-consuming process with considerable variations in diagnosis between the experts. This paper presents a computer aided decision support system (CADSS) tool to help the pathologists in their examination of the cervical cancer biopsies. The main aim of the proposed CADSS system is to identify abnormalities and quantify cancer grading in a systematic and repeatable manner. The paper proposes three different methods which presents and compares the results using 475 images of cervical biopsies which include normal, three stages of pre cancer, and malignant cases. This paper will explore various components of an effective CADSS; image acquisition, pre-processing, segmentation, feature extraction, classification, grading and disease identification. Cervical histological images are captured using a digital microscope. The images are captured in sufficient resolution to retain enough information for effective classification. Histology images of cervical biopsies consist of three major sections; background, stroma and squamous epithelium. Most diagnostic information are contained within the epithelium region. This paper will present two levels of segmentations; global (macro) and local (micro). At the global level the squamous epithelium is separated from the background and stroma. At the local or cellular level, the nuclei and cytoplasm are segmented for further analysis. Image features that influence the pathologists’ decision during the analysis and classification of a cervical biopsy are the nuclei’s shape and spread; the ratio of the areas of nuclei and cytoplasm as well as the texture and spread of the abnormalities. Similar features are extracted towards the automated classification process. This paper will present various feature extraction methods including colour, shape and texture using Gabor wavelet as well as various quantative metrics. Generated features are used to classify cells or regions into normal and abnormal categories. Following the classification process, the cancer is graded based on the spread of the abnormal cells. This paper will present the results of the grading process with five stages of the cancer spectrum.

Proceedings Article | 3 September 2009 Paper

A generic approach to haptic modeling of textile artifacts

H. Shidanshidi, F. Naghdy, G. Naghdy, D. Wood Conroy

Proceedings Volume 7444, 74440G (2009) https://doi.org/10.1117/12.829096

KEYWORDS: 3D modeling, Haptic technology, Statistical modeling, 3D image processing, Fuzzy logic, Digital image processing, Neural networks, Virtual reality, Algorithm development, Raw materials

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Proceedings Article | 26 February 2008 Paper

3D geometric modelling of hand-woven textile

H. Shidanshidi, F. Naghdy, G. Naghdy, D. Wood Conroy

Proceedings Volume 6813, 68130B (2008) https://doi.org/10.1117/12.784603

KEYWORDS: 3D modeling, Fuzzy logic, Haptic technology, Algorithm development, Systems modeling, Detection and tracking algorithms, Pattern recognition, Modeling, Data modeling, Visual process modeling

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Proceedings Article | 24 August 2006 Paper

Resolution modification and context based image processing for retinal prosthesis

Golshah Naghdy, Chris Beston, Jong-Mo Seo, Hum Chung

Proceedings Volume 6312, 631203 (2006) https://doi.org/10.1117/12.675624

KEYWORDS: Eye, Retina, Image resolution, Image processing, Spatial resolution, Electrodes, Cameras, Visualization, Luminescence, Spectral resolution

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Proceedings Article | 24 June 2005 Paper

Scalable multiresolution color image segmentation

Farin Akhlaghian Tab, Golshah Naghdy, Alfred Mertins

Proceedings Volume 5960, 59604X (2005) https://doi.org/10.1117/12.633217

KEYWORDS: Image segmentation, Image resolution, Image processing algorithms and systems, Wavelets, Image processing, Scalable video coding, Color image segmentation, Wavelet transforms, Spatial resolution, Magnetorheological finishing

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Proceedings Article | 12 May 2004 Paper

Method for breast cancer classification based solely on morphological descriptors

Catherine Todd, Golshah Naghdy

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.533938

KEYWORDS: Image segmentation, Feature extraction, Mammography, Fuzzy logic, Breast, Image processing, Tissues, Distance measurement, Breast cancer, Detection and tracking algorithms

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Proceedings Article | 15 May 2003 Paper

Wavelet-morphology for mass detection in digital mammogram images

Golshah Naghdy, Yue Li, Jian Wang

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.480109

KEYWORDS: Mammography, Wavelet transforms, Wavelets, Image processing, Image segmentation, Image enhancement, Feature extraction, Image processing algorithms and systems, Tissues, Image analysis

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Proceedings Article | 8 July 1999 Paper

Detection of microcalcification in computer-assisted mammogram analysis

Golshah Naghdy, Fazel Naghdy, L. Yue, A. Drijarkara

Proceedings Volume 3747, (1999) https://doi.org/10.1117/12.351623

KEYWORDS: Mammography, Wavelets, Fuzzy logic, Signal processing, Image processing, Signal detection, Sensors, Databases, Neural networks, Algorithm development

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SPIE Journal Paper | 1 July 1997

Wavelet-based feature-adaptive adaptive resonance theory neural network for texture identification

Jian Wang, Golshah Naghdy, Philip Ogunbona

JEI, Vol. 6, Issue 03, (July 1997) https://doi.org/10.1117/12.10.1117/12.269902

KEYWORDS: Neural networks, Wavelets, Fuzzy logic, Visual system, Image classification, Visual process modeling, Classification systems, Systems modeling, Feature extraction, Binary data

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Proceedings Article | 22 April 1996 Paper

Texture analysis using Gabor wavelets

Golshah Naghdy, Jian Wang, Philip Ogunbona

Proceedings Volume 2657, (1996) https://doi.org/10.1117/12.238703

KEYWORDS: Wavelets, Image classification, Image filtering, Visual cortex, Fourier transforms, Signal processing, Filtering (signal processing), Wavelet transforms, Signal analysis, Visual system

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Proceedings Article | 20 August 1993 Paper

Adaptation of Gabor filters for simulation of human preattentive mechanism for a mobile robot

Naren Kulkarni, Golshah Naghdy

Proceedings Volume 2055, (1993) https://doi.org/10.1117/12.150164

KEYWORDS: Image filtering, Robot vision, Robots, Machine vision, Spatial frequencies, Fourier transforms, Image segmentation, Spatial resolution, Visual system, Computer vision technology

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Showing 5 of 11 publications

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