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3 "Image Processing"
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Original Articles
Difference of the Nuclear Green Light Intensity between Papillary Carcinoma Cells Showing Clear Nuclei and Non-neoplastic Follicular Epithelia in Papillary Thyroid Carcinoma
Hyekyung Lee, Tae Hwa Baek, Meeja Park, Seung Yun Lee, Hyun Jin Son, Dong Wook Kang, Joo Heon Kim, Soo Young Kim
J Pathol Transl Med. 2016;50(5):355-360.   Published online August 22, 2016
DOI: https://doi.org/10.4132/jptm.2016.05.19
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  • 89 Download
AbstractAbstract PDF
Background
There is subjective disagreement regarding nuclear clearing in papillary thyroid carcinoma. In this study, using digital instruments, we were able to quantify many ambiguous pathologic features and use numeric data to express our findings.
Methods
We examined 30 papillary thyroid carcinomas. For each case, we selected representative cancer cells showing clear nuclei and surrounding non-neoplastic follicular epithelial cells and evaluated objective values of green light intensity (GLI) for quantitative analysis of nuclear clearing in papillary thyroid carcinoma.
Results
From 16,274 GLI values from 600 cancer cell nuclei and 13,752 GLI values from 596 non-neoplastic follicular epithelial nuclei, we found a high correlation of 94.9% between GLI and clear nuclei. GLI between the cancer group showing clear nuclei and non-neoplastic follicular epithelia was statistically significant. The overall average level of GLI in the cancer group was over two times higher than the non-neoplastic group despite a wide range of GLI. On a polygonal line graph, there was a fluctuating unique difference between both the cancer and non-neoplastic groups in each patient, which was comparable to the microscopic findings.
Conclusions
Nuclear GLI could be a useful factor for discriminating between carcinoma cells showing clear nuclei and non-neoplastic follicular epithelia in papillary thyroid carcinoma.
Nuclear Image Analysis Study of Neuroendocrine Tumors
Meeja Park, Taehwa Baek, Jongho Baek, Hyunjin Son, Dongwook Kang, Jooheon Kim, Hyekyung Lee
Korean J Pathol. 2012;46(1):38-41.   Published online February 23, 2012
DOI: https://doi.org/10.4132/KoreanJPathol.2012.46.1.38
  • 6,281 View
  • 40 Download
  • 2 Crossref
AbstractAbstract PDF
Background

There is a subjective disagreement about nuclear chromatin in the field of pathology. Objective values of red, green, and blue (RGB) light intensities for nuclear chromatin can be obtained through a quantitative analysis using digital images.

Methods

We examined 10 cases of well differentiated neuroendocrine tumors of the rectum, small cell lung carcinomas, and moderately differentiated squamous cell lung carcinomas respectively. For each case, we selected 30 representative cells and captured typical microscopic findings. Using an image analyzer, we determined the longest nuclear line profiles and obtained graph files and Excel data on RGB light intensities. We assessed the meaningful differences in graph files and Excel data among the three different tumors.

Results

The nucleus of hematoxylin and eosin-stained tumor cells was expressed as a combination of RGB light sources. The highest intensity was from blue, whereas the lowest intensity was from green. According to the graph files, green showed the most noticeable change in the light intensity, which is consistent with the difference in standard deviations.

Conclusions

The change in the light intensity for green has an important implication for differentiating between tumors. Specific features of the nucleus can be expressed in specific values of RGB light intensities.

Citations

Citations to this article as recorded by  
  • Difference of the Nuclear Green Light Intensity between Papillary Carcinoma Cells Showing Clear Nuclei and Non-neoplastic Follicular Epithelia in Papillary Thyroid Carcinoma
    Hyekyung Lee, Tae Hwa Baek, Meeja Park, Seung Yun Lee, Hyun Jin Son, Dong Wook Kang, Joo Heon Kim, Soo Young Kim
    Journal of Pathology and Translational Medicine.2016; 50(5): 355.     CrossRef
  • Comparison of diagnostic accuracy between CellprepPlus® and ThinPrep® liquid‐based preparations in effusion cytology
    Yong‐Moon Lee, Ji‐Yong Hwang, Seung‐Myoung Son, Song‐Yi Choi, Ho‐Chang Lee, Eun‐Joong Kim, Hye‐Suk Han, Jin young An, Joung‐Ho Han, Ok‐Jun Lee
    Diagnostic Cytopathology.2014; 42(5): 384.     CrossRef
A Study on an Automatic Detection of Uterine Cervical Pap-smears by Image Processing.
Sung Kyung Un, Chan Mo Park, Hwa Choon Park, So Young Yoon, Min Sun Cho, Soo Yeon Cho, Sung Sook Kim
Korean J Cytopathol. 1994;5(1):15-22.
  • 1,683 View
  • 11 Download
AbstractAbstract PDF
Cancer of the cervix is the most common malignancy in women in developing countries and the second most common cancer in women throughout the world with approximately 500,000 new cases each year. Prevention of this large number of premature deaths among women is, therefore, a goal worthy of urgent and serious consideration. In this thesis, an automatic cancerous nucleus detection method essential to a screening system with Papanicolaou stained specimens called Pap-smear is proposed which employs image processing techniques. It uses edge information to segment objects and morphologic as well as densitometric information to distinguish cancerous nuclei from dirts or normal nuclei. It has produced useful results in our study.

J Pathol Transl Med : Journal of Pathology and Translational Medicine
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