Predicting grade of prostate cancer using image analysis software

V. Guru Anand; G. Hari Krishna; G. Mohandass; R. J. Hemalatha; Sandhya Sundaram

doi:10.1109/TISC.2010.5714621

Predicting grade of prostate cancer using image analysis software

V. Guru Anand
, G. Hari Krishna
, G. Mohandass
, R. J. Hemalatha
, Sandhya Sundaram

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

16 Scopus citations

Abstract

The prognosis of prostate cancer is determined by using the Gleason grading system. This grading is done based upon the tissue pattern obtained from the tumor, after staining the biopsy with Heamatoxylin and Eosin (H&E). Presently, experienced pathologists manually grade on prostate cancers subjectively. The grading therefore depends upon the experience of the pathologists, quality of the staining and various other factors. To overcome this, an image analysis system is developed using MATLAB that can examine the biopsy image and grade it objectively. Size distribution of the sample image is utilized to recognize the pattern. The prediction is done based on the pattern of lumen, nuclei and the glandular organization in the representative areas of biopsy-image taken from a microscope. The results obtained show a remarkable accuracy and is closer to the manual grading scores. This Computer-Adaptive- Diagnosis (CAD) system may be used as a powerful adjunct for effectively diagnosing the prostate cancers and grading them.

Original language	English (US)
Title of host publication	Proceedings of the 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010
Pages	122-124
Number of pages	3
DOIs	https://doi.org/10.1109/TISC.2010.5714621
State	Published - 2010
Event	2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010 - Chennai, India Duration: Dec 17 2010 → Dec 19 2010

Publication series

Name	Proceedings of the 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010

Other

Other	2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010
Country/Territory	India
City	Chennai
Period	12/17/10 → 12/19/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Gleason grading
Heamatoxylin and Eosin (H&E)
Pattern recognition
Prostate cancer

Publisher link

10.1109/TISC.2010.5714621

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Guru Anand, V., Hari Krishna, G., Mohandass, G., Hemalatha, R. J., & Sundaram, S. (2010). Predicting grade of prostate cancer using image analysis software. In Proceedings of the 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010 (pp. 122-124). Article 5714621 (Proceedings of the 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010). https://doi.org/10.1109/TISC.2010.5714621

Predicting grade of prostate cancer using image analysis software. / Guru Anand, V.; Hari Krishna, G.; Mohandass, G. et al.
Proceedings of the 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010. 2010. p. 122-124 5714621 (Proceedings of the 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Guru Anand, V, Hari Krishna, G, Mohandass, G, Hemalatha, RJ & Sundaram, S 2010, Predicting grade of prostate cancer using image analysis software. in Proceedings of the 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010., 5714621, Proceedings of the 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010, pp. 122-124, 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010, Chennai, India, 12/17/10. https://doi.org/10.1109/TISC.2010.5714621

Guru Anand V, Hari Krishna G, Mohandass G, Hemalatha RJ, Sundaram S. Predicting grade of prostate cancer using image analysis software. In Proceedings of the 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010. 2010. p. 122-124. 5714621. (Proceedings of the 2nd International Conference on Trendz in Information Sciences and Computing, TISC-2010). doi: 10.1109/TISC.2010.5714621

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abstract = "The prognosis of prostate cancer is determined by using the Gleason grading system. This grading is done based upon the tissue pattern obtained from the tumor, after staining the biopsy with Heamatoxylin and Eosin (H\&E). Presently, experienced pathologists manually grade on prostate cancers subjectively. The grading therefore depends upon the experience of the pathologists, quality of the staining and various other factors. To overcome this, an image analysis system is developed using MATLAB that can examine the biopsy image and grade it objectively. Size distribution of the sample image is utilized to recognize the pattern. The prediction is done based on the pattern of lumen, nuclei and the glandular organization in the representative areas of biopsy-image taken from a microscope. The results obtained show a remarkable accuracy and is closer to the manual grading scores. This Computer-Adaptive- Diagnosis (CAD) system may be used as a powerful adjunct for effectively diagnosing the prostate cancers and grading them.",

keywords = "Gleason grading, Heamatoxylin and Eosin (H\&E), Pattern recognition, Prostate cancer",

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AU - Mohandass, G.

AU - Hemalatha, R. J.

AU - Sundaram, Sandhya

PY - 2010

Y1 - 2010

N2 - The prognosis of prostate cancer is determined by using the Gleason grading system. This grading is done based upon the tissue pattern obtained from the tumor, after staining the biopsy with Heamatoxylin and Eosin (H&E). Presently, experienced pathologists manually grade on prostate cancers subjectively. The grading therefore depends upon the experience of the pathologists, quality of the staining and various other factors. To overcome this, an image analysis system is developed using MATLAB that can examine the biopsy image and grade it objectively. Size distribution of the sample image is utilized to recognize the pattern. The prediction is done based on the pattern of lumen, nuclei and the glandular organization in the representative areas of biopsy-image taken from a microscope. The results obtained show a remarkable accuracy and is closer to the manual grading scores. This Computer-Adaptive- Diagnosis (CAD) system may be used as a powerful adjunct for effectively diagnosing the prostate cancers and grading them.

AB - The prognosis of prostate cancer is determined by using the Gleason grading system. This grading is done based upon the tissue pattern obtained from the tumor, after staining the biopsy with Heamatoxylin and Eosin (H&E). Presently, experienced pathologists manually grade on prostate cancers subjectively. The grading therefore depends upon the experience of the pathologists, quality of the staining and various other factors. To overcome this, an image analysis system is developed using MATLAB that can examine the biopsy image and grade it objectively. Size distribution of the sample image is utilized to recognize the pattern. The prediction is done based on the pattern of lumen, nuclei and the glandular organization in the representative areas of biopsy-image taken from a microscope. The results obtained show a remarkable accuracy and is closer to the manual grading scores. This Computer-Adaptive- Diagnosis (CAD) system may be used as a powerful adjunct for effectively diagnosing the prostate cancers and grading them.

KW - Gleason grading

KW - Heamatoxylin and Eosin (H&E)

KW - Pattern recognition

KW - Prostate cancer

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ER -

Predicting grade of prostate cancer using image analysis software

Abstract

Publication series

Other

UN SDGs

Keywords

Publisher link

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