Classification of benign endometrial glandular cells in cervical smears from postmenopausal women

Cancer ◽  
2002 ◽  
Vol 96 (2) ◽  
pp. 60-66 ◽  
Author(s):  
Edi Brogi ◽  
Rosemary Tambouret ◽  
Debra A. Bell
2001 ◽  
Vol 45 (2) ◽  
pp. 153-156 ◽  
Author(s):  
Venetia R. Sarode ◽  
Anne E. Rader ◽  
Peter G. Rose ◽  
Michael Rodriguez ◽  
Fadi W. Abdul-Karim

1995 ◽  
pp. 113-131
Author(s):  
Mathilde E. Boon ◽  
L. P. Kok
Keyword(s):  

1999 ◽  
Vol 123 (5) ◽  
pp. 404-410
Author(s):  
Hidejiro Yokoo ◽  
M. Irtaza Usman ◽  
Susan Wheaton ◽  
Patricia A. Kampmeier

Abstract Background.—The histologic classification of colorectal polyps is well established. However, practicing pathologists may still occasionally encounter colorectal polyps that are difficult to classify. We studied 6 colorectal polyps that showed uncommon histologic features that have not been described in the English language literature. Materials and Methods.—The polyps were studied using standard hematoxylin-eosin stain, mucin histochemistry, and electron microscopy. Results.—The 6 polyps we studied showed extensive papillary and villous structures with alternating villi and crypts. The villi were lined by well-differentiated absorptive cells, whereas the crypts were lined by immature glandular cells, thus mimicking the histology of the small intestinal mucosa. Conclusions.—These polyps appear to represent a variant of the hyperplastic polyp, in as much as cellular maturation (immature glandular cells differentiate into the mature surface absorptive cells) is the essential feature distinguishing hyperplastic polyps from adenomas.


2014 ◽  
Vol 58 (1) ◽  
pp. 42-46 ◽  
Author(s):  
Gozde Kir ◽  
Muberra Segmen Yilmaz ◽  
Handan Çetiner ◽  
Ahmet Gocmen ◽  
Filiz Alptekin

2003 ◽  
Vol 47 (2) ◽  
pp. 135-140 ◽  
Author(s):  
Ping Wen ◽  
Caroline M. Abramovich ◽  
Nancy Wang ◽  
Natalie Knop ◽  
Sallie Mansbacher ◽  
...  

2020 ◽  
Vol 53 (3-4) ◽  
pp. 184-190
Author(s):  
Ramaiah Arun ◽  
Shanmugasundaram Singaravelan

One of the biggest challenges the world face today is the mortality due to Cancer. One in four of all diagnosed cancers involve the lung cancer, where the mortality rate is high, even after so much of technical and medical advances. Most lung cancer cases are diagnosed either in the third or fourth stage, when the disease is not treatable. The main reason for the highest mortality, due to lung cancer is because of non availability of prescreening system which can analyze the cancer cells at early stages. So it is necessary to develop a prescreening system which helps doctors to find and detect lung cancer at early stages. Out of all various types of lung cancers, adenocarcinoma is increasing at an alarming rate. The reason is mainly attributed to the increased rate of smoking - both active and passive. In the present work, a system for the classification of lung glandular cells for early detection of Cancer using multiple color spaces is developed. For segmentation, various clustering techniques like K-Means clustering and Fuzzy C-Means clustering on various Color spaces such as HSV, CIELAB, CIEXYy and CIELUV are used. Features are Extracted and classified using Support Vector Machine (SVM).


2009 ◽  
Vol 43 (5) ◽  
pp. 453 ◽  
Author(s):  
Yi Kyeong Chun ◽  
Sung Ran Hong ◽  
Hye Sun Kim ◽  
Ji Young Kim ◽  
Hy Sook Kim

2002 ◽  
Vol 78 (3) ◽  
pp. 227-234 ◽  
Author(s):  
C.I. Parellada ◽  
P.L. Schivartche ◽  
E.A. Pereyra ◽  
A.C. Chuery ◽  
S.M.G. Mioni ◽  
...  

2001 ◽  
Vol 24 (4) ◽  
pp. 271-275 ◽  
Author(s):  
Rosemary Tambouret ◽  
Debra A. Bell ◽  
Barbara A. Centeno

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