Prof. Daron G. Ferris Profile

Prof. Daron G. Ferris

at Medical College of Georgia

SPIE Involvement:

Author

Publications (8)

SPIE Journal Paper | 1 January 2009 Open Access

Using acetowhite opacity index for detecting cervical intraepithelial neoplasia

Wenjing Li, Sankar Venkataraman, Ulf Gustafsson, Jody Oyama, Daron Ferris, Rich Lieberman

JBO, Vol. 14, Issue 01, 014020, (January 2009) https://doi.org/10.1117/12.10.1117/1.3079810

KEYWORDS: Opacity, Cervix, Tissues, Image segmentation, Expectation maximization algorithms, Image analysis, Detection and tracking algorithms, Lithium, Human subjects, Image processing

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Proceedings Article | 11 March 2008 Paper

Computerized image analysis for acetic acid induced intraepithelial lesions

Wenjing Li, Daron Ferris, Rich Lieberman

Proceedings Volume 6914, 69143A (2008) https://doi.org/10.1117/12.769298

KEYWORDS: Opacity, Image analysis, Tissues, Image processing, Human subjects, Image registration, Cervix, Digital imaging, Algorithm development, Visualization

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Proceedings Article | 30 March 2007 Paper

Automated image analysis of uterine cervical images

Wenjing Li, Jia Gu, Daron Ferris, Allen Poirson

Proceedings Volume 6514, 65142P (2007) https://doi.org/10.1117/12.708710

KEYWORDS: Cervix, Cervical cancer, Image segmentation, Cancer, Expectation maximization algorithms, Image analysis, Computer aided diagnosis and therapy, Diagnostics, Calibration, Feature extraction

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Proceedings Article | 29 April 2005 Paper

Computer-aided-diagnosis (CAD) for colposcopy

Holger Lange, Daron Ferris

Proceedings Volume 5747, (2005) https://doi.org/10.1117/12.594658

KEYWORDS: Algorithm development, Feature extraction, Cervical cancer, Cervix, Image processing, CAD systems, Tissues, Image analysis, Computer aided diagnosis and therapy, Computing systems

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Uterine cervical cancer is the second most common cancer among women worldwide. Colposcopy is a diagnostic method, whereby a physician (colposcopist) visually inspects the lower genital tract (cervix, vulva and vagina), with special emphasis on the subjective appearance of metaplastic epithelium comprising the transformation zone on the cervix. Cervical cancer precursor lesions and invasive cancer exhibit certain distinctly abnormal morphologic features. Lesion characteristics such as margin; color or opacity; blood vessel caliber, intercapillary spacing and distribution; and contour are considered by colposcopists to derive a clinical diagnosis. Clinicians and academia have suggested and shown proof of concept that automated image analysis of cervical imagery can be used for cervical cancer screening and diagnosis, having the potential to have a direct impact on improving women’s health care and reducing associated costs. STI Medical Systems is developing a Computer-Aided-Diagnosis (CAD) system for colposcopy -- ColpoCAD. At the heart of ColpoCAD is a complex multi-sensor, multi-data and multi-feature image analysis system. A functional description is presented of the envisioned ColpoCAD system, broken down into: Modality Data Management System, Image Enhancement, Feature Extraction, Reference Database, and Diagnosis and directed Biopsies. The system design and development process of the image analysis system is outlined. The system design provides a modular and open architecture built on feature based processing. The core feature set includes the visual features used by colposcopists. This feature set can be extended to include new features introduced by new instrument technologies, like fluorescence and impedance, and any other plausible feature that can be extracted from the cervical data. Preliminary results of our research on detecting the three most important features: blood vessel structures, acetowhite regions and lesion margins are shown. As this is a new and very complex field in medical image processing, the hope is that this paper can provide a framework and basis to encourage and facilitate collaboration and discussion between industry, academia, and medical practitioners.

Proceedings Article | 29 April 2005 Paper

A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features

Yeshwanth Srinivasan, Dana Hernes, Bhakti Tulpule, Shuyu Yang, Jiangling Guo, Sunanda Mitra, Sriraja Yagneswaran, Brian Nutter, Jose Jeronimo, Benny Phillips, Rodney Long, Daron Ferris

Proceedings Volume 5747, (2005) https://doi.org/10.1117/12.597075

KEYWORDS: Image segmentation, Cervix, Image classification, Chromium, Cancer, Cervical cancer, Diagnostics, Image processing, Library classification systems, Binary data

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Proceedings Article | 12 May 2004 Paper

A multispectral digital Cervigram analyzer in the wavelet domain for early detection of cervical cancer

Shuyu Yang, Jiangling Guo, Philip King, Y. Sriraja, Sunanda Mitra, Brian Nutter, Daron Ferris, Mark Schiffman, Jose Jeronimo, Rodney Long

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.537622

KEYWORDS: Image segmentation, Image compression, Cervix, Cervical cancer, Quantization, Image registration, Image processing, Medical imaging, Cancer, Image analysis

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Proceedings Article | 12 May 2004 Open Access

Analysis of digitized cervical images to detect cervical neoplasia

Daron Ferris

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.544313

KEYWORDS: Image segmentation, Cervical cancer, Image analysis, Image registration, Cervix, Reflectance spectroscopy, Image compression, Reflectivity, Cancer, Image processing algorithms and systems

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Proceedings Article | 2 July 2001 Paper

Multimodal multispectral imaging of the cervix in vivo for the detection of neoplasia

Anant Agrawal, Tim Harrell, Shabbir Bambot, Mark Faupel, Daron Ferris

Proceedings Volume 4259, (2001) https://doi.org/10.1117/12.432482

KEYWORDS: Cervix, Luminescence, Tissues, Reflectivity, In vivo imaging, Imaging systems, Brain-machine interfaces, Ultraviolet radiation, Multispectral imaging, Optical filters

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Showing 5 of 8 publications

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