• 대한세포병리학회지
• /
• 제7권1호
• /
• pp.23-30
• /
• 1996

Chromatin texture, which partly reflects nuclear organization, is evolving as an important parameter indicating cell activation or transformation. In this study, chromatin pattern was evaluated by image analysis of the electron micrographs of follicular and papillary carcinoma cells of the thyroid gland and tested for discrimination of the two neoplasms. Digital grey images were converted from the electron micrographs, nuclear images, excluding nucleolus and intranuclear cytoplasmic inclusions, were obtained by segmentation; grey levels were standardized; and grey level histograms were generated. The histograms in follicular carcinoma showed Gaussian or near-Gaussian distribution and had a single peak, whereas those in papillary carcinoma had two peaks(bimodal), one at the black zone and the other at the white zone. In papillary carcinoma, the peak in the black zone represented an increased amount of heterochromatin particles and that at the white zone represented decreased electron density of euchromatin or nuclear matrix. These results indicate that the nuclei of follicular and papillary carcinoma cells differ in their chromatin pattern and the difference may be due to decondensed chromatin and/or matrix substances.

• 한국컴퓨터정보학회논문지
• /
• 제16권10호
• /
• pp.83-92
• /
• 2011

본 연구의 목적은 세포핵의 3차원 염색질 질감 특성값이 암의 진행정도를 인식하는데 있어 유용한 특성값인지 평가하는데 있다. 특히, 제안한 방법이 악성이라고 진단된 세포진 도말 표본에서 정상으로 보이는 세포의 염색질 패턴에서의 미세한 차이를 인식할 수 있는지 살펴보고자 한다. 분류등급 정상(Normal), 저등급 편평 상피내 병변(LSIL, Low grade Squamous Intraepithelial Lesion), 고등급 편평 상피내 병변(HSIL, High grade Squamous Intraepithelial Lesion)에서 각각 100개씩의 세포 볼륨데이터로부터 3차원 GLCM(Gray Level Co occurrence Matrix)에 기반한 질감 특성값과 3차원 Wavelet 변환에 기반한 질감 특성값을 추출하고 분류기를 생성한 후 각 분류기에 대한 분류정확도를 비교하였으며, 2차원 세포진 영상에서의 세포핵 질감 특성값과 비교하기 위해 동일한 실험 볼륨데이터의 투영된 2차원 영상을 이용하여 같은 방법으로 2차원 세포핵 질감 특성값을 추출하고 분류기를 생성한 후 분류정확도를 비교하였다. 2차원 세포핵 질감 특성값과의 비교연구에서 3차원 세포핵 질감 특성값이 등급별 분류에 있어 보다 효율적인 것을 확인 할 수 있었으며 이는 3차원 염색질 질감 특성값이 자궁경부 세포의 정량화에 대한 정확성과 재현성을 개선할 수 있음을 의미한다.

• 한국멀티미디어학회논문지
• /
• 제11권12호
• /
• pp.1635-1648
• /
• 2008

The extraction of important features in cancer cell image analysis is a key process in grading renal cell carcinoma. In this study, we applied three-dimensional (3D) texture feature extraction methods to cell nuclei images and evaluated the validity of them for computerized cell nuclei grading. Individual images of 2,423 cell nuclei were extracted from 80 renal cell carcinomas (RCCs) using confocal laser scanning microscopy (CLSM). First, we applied the 3D texture mapping method to render the volume of entire tissue sections. Then, we determined the chromatin texture quantitatively by calculating 3D gray-level co-occurrence matrices (3D GLCM) and 3D run length matrices (3D GLRLM). Finally, to demonstrate the suitability of 3D texture features for grading, we performed a discriminant analysis. In addition, we conducted a principal component analysis to obtain optimized texture features. Automatic grading of cell nuclei using 3D texture features had an accuracy of 78.30%. Combining 3D textural and 3D morphological features improved the accuracy to 82.19%. As a comparative study, we also performed a stepwise feature selection. Using the 4 optimized features, we could obtain more improved accuracy of 84.32%. Three dimensional texture features have potential for use as fundamental elements in developing a new nuclear grading system with accurate diagnosis and predicting prognosis.