Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 109

1.

Segmentation of transitional cell carcinoma nuclei by nonsupervised thresholding in different color spaces.

Pavlopoulos PM, Zimeras S, Kavantzas N, Korkolopoulou P, Agapitos E, Patsouris E.

Anal Quant Cytol Histol. 2007 Aug;29(4):271-8.

PMID:
17879636
2.
3.

Automated cell nuclear segmentation in color images of hematoxylin and eosin-stained breast biopsy.

Latson L, Sebek B, Powell KA.

Anal Quant Cytol Histol. 2003 Dec;25(6):321-31.

PMID:
14714298
4.

Automated segmentation of routinely hematoxylin-eosin-stained microscopic images by combining support vector machine clustering and active contour models.

Glotsos D, Spyridonos P, Cavouras D, Ravazoula P, Dadioti PA, Nikiforidis G.

Anal Quant Cytol Histol. 2004 Dec;26(6):331-40.

PMID:
15678615
5.

Automatic segmentation of cell nuclei in Feulgen-stained histological sections of prostate cancer and quantitative evaluation of segmentation results.

Nielsen B, Albregtsen F, Danielsen HE.

Cytometry A. 2012 Jul;81(7):588-601. doi: 10.1002/cyto.a.22068. Epub 2012 May 17.

6.
7.

Morphometry of bladder carcinoma: definition of a new variable.

Sowter C, Sowter G, Slavin G, Rosen D.

Anal Cell Pathol. 1990 Jul;2(4):205-13.

PMID:
2275868
8.

Automatic segmentation of cell nuclei in bladder and skin tissue for karyometric analysis.

Korde VR, Bartels H, Barton J, Ranger-Moore J.

Anal Quant Cytol Histol. 2009 Apr;31(2):83-9.

9.

Learning-based Method for P53 Immunohistochemically Stained Cell Image Segmentation.

Mao K, Zhao P, Tan PH.

Conf Proc IEEE Eng Med Biol Soc. 2005;3:3264-7.

PMID:
17282942
10.

Prognostic significance of nuclear morphometry in superficial bladder cancer.

Ozer E, Yörükoğlu K, Mungan MU, Ozkal S, Demirel D, Sağol O, Kirkali Z.

Anal Quant Cytol Histol. 2001 Aug;23(4):251-6.

PMID:
11531139
11.

An entropy-based automated cell nuclei segmentation and quantification: application in analysis of wound healing process.

Oswal V, Belle A, Diegelmann R, Najarian K.

Comput Math Methods Med. 2013;2013:592790. doi: 10.1155/2013/592790. Epub 2013 Mar 5.

12.

Computer-based grading of haematoxylin-eosin stained tissue sections of urinary bladder carcinomas.

Spyridonos P, Ravazoula P, Cavouras D, Berberidis K, Nikiforidis G.

Med Inform Internet Med. 2001 Jul-Sep;26(3):179-90.

PMID:
11706928
13.
14.

Multi-level adaptive segmentation of multi-parameter MR brain images.

Zavaljevski A, Dhawan AP, Gaskil M, Ball W, Johnson JD.

Comput Med Imaging Graph. 2000 Mar-Apr;24(2):87-98.

PMID:
10767588
15.

Performance evaluation of maximal separation techniques in immunohistochemical scoring of tissue images.

Hameed KA, Banumathi A, Ulaganathan G.

Micron. 2015 Dec;79:29-35. doi: 10.1016/j.micron.2015.07.013. Epub 2015 Aug 5.

PMID:
26313715
16.

Multivariate classifications of transitional cell tumors of the bladder: nuclear abnormality index and pattern recognition analysis.

Montironi R, Scarpelli M, Pisani E, Ansuini G, Collina G, Mariuzzi GM, Collan Y.

Appl Pathol. 1986;4(1-2):48-54.

PMID:
3555547
17.

Neural network-based segmentation and classification system for automated grading of histologic sections of bladder carcinoma.

Spyridonos P, Cavouras D, Ravazoula P, Nikiforidis G.

Anal Quant Cytol Histol. 2002 Dec;24(6):317-24.

PMID:
12508689
18.

Potential of radial basis function neural networks in discriminating benign from malignant lesions of the lower urinary tract.

Karakitsos P, Pouliakis A, Kordalis G, Georgoulakis J, Kittas C, Kyroudes A.

Anal Quant Cytol Histol. 2005 Feb;27(1):35-42.

PMID:
15794450
19.

[A nucleus area extraction method for image analysis of kidney-tissue slice].

Zhang J, Zhu H.

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2007 Aug;24(4):923-7. Chinese.

PMID:
17899775
20.

Grading of transitional cell bladder carcinoma by image analysis of histological sections.

Jarkrans T, Vasko J, Bengtsson E, Choi HK, Malmström PU, Wester K, Busch C.

Anal Cell Pathol. 1995 Mar;8(2):135-58.

PMID:
7786812

Supplemental Content

Support Center