The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia

Human Pathology

Volumn 35, Issue 9, 2004, Pages 1121-1131

  Diamond, James ^a   Anderson, Neil H ^b   Bartels, Peter H ^c   Montironi, Rodolfo ^d   Hamilton, Peter W ^a  

^a QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

^b ROYAL VICTORIA HOSPITAL   (United Kingdom)

^c UNIVERSITY OF ARIZONA   (United States)

^d UNIVERSITÀ POLITECNICA DELLE MARCHE   (Italy)

Author keywords

H4; Haralick feature 4; histopathology; imaging; PCa; PIN; prostate; prostatic carcinoma; prostatic intraepithelial neoplasia; texture analysis

Indexed keywords

ARTICLE; AUTOMATION; CONTROLLED STUDY; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; IMAGE PROCESSING; MALE; METHODOLOGY; MORPHOLOGY; PROSTATE CARCINOMA; PROSTATE TUMOR; PROSTATECTOMY; QUANTITATIVE ANALYSIS; STROMA; VALIDATION PROCESS;

HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; PROSTATIC NEOPLASMS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 4444356703     PISSN: 00468177     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.humpath.2004.05.010     Document Type: Article

References (24)

1. The Institute of Cancer Research. Prostate cancer set to become the most common men's cancer within three years. 2002;. [press release]. May 27
2. O'Leary T.J., Tellado M., Bruckner S.B., et al. PAPNET-assisted rescreening of cervical smears Cost and accuracy compared with 100% manual rescreening strategy. JAMA. 279:1998;235-237
3. Patten S.F., Lee J.S., Nelson A.C. NeoPath AutoPap 300 automated Pap screener system. Acta Cytol. 40:1996;45-52
4. Thompson D., Bartels P.H., Bartels H., et al. Knowledge-based segmentation of colorectal histologic imagery. Anal Quant Cytol Histol. 15:1993;236-246
5. Hamilton P.W., Thompson D., Sloan J., et al. Knowledge-guided segmentation and morphometric analysis of colorectal dysplasia. Anal Quant Cytol Histol. 17:1995;172-182
6. Bartels P.H., Thompson D., Bartels H., et al. Machine vision-based histometry of premalignant and malignant prostatic lesions. Pathol Res Pract. 191:1995;935-944
7. Thompson D., Bartels P.H., Bartels H., et al. Image segmentation of cribriform gland tissue. Anal Quant Cytol Histol. 17:1995;314-322
8. Anderson N.H., Hamilton P.W., Bartels P.H., et al. Computerized scene segmentation for the discrimination of architectural features in proliferative lesions of the breast. J Pathol. 181:1997;374-380
9. Keenan S., Diamond J., McCluggage W.G., et al. An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (CIN). J Pathol. 192:2000;351-362
10. Baak J.P.A. The framework of pathology Good laboratory practice by quantitative and molecular methods. J Pathol. 198:2002;277-283
11. Julesz B. Texture and visual perception. Sci Am. 212:1965;38-48
12. Richard W.D., Keen C.G. Automated texture-based segmentation of ultrasound images of the prostate. Comput Med Imaging Graph. 20:1996;131-140
13. Basset O., Sun Z., Mestas J.L., et al. Texture analysis of ultrasonic images of the prostate by means of co-occurrence matrices. Ultrason Imaging. 15:1993;218-237
14. Christen R., Xiao J., Ninimo C., et al. Chromatin texture features in hematoxylin and eosin-stained prostate tissue. Anal Quant Cytol Histol. 15:1993;383-388
15. Bartels P.H., Montironi R., Hamilton P.W., et al. Nuclear chromatin texture in prostatic lesions: 1. PIN and adenocarcinoma. Anal Quant Cytol Histol. 20:1998;389-396
16. Bartels P.H., Montironi R., Hamilton P.W., et al. Nuclear chromatin texture in prostatic lesions: 2. PIN and malignancy-associated changes. Anal Quant Cytol Histol. 20:1998;397-406
17. Hamilton P.W., Bartels P.H., Thompson D., et al. Automated location of dysplastic fields in colorectal histology using image texture analysis. J Pathol. 182:1997;68-75
18. Hamilton P.W., Bartels P.H., Montironi R., et al. Automated histometry in quantitative prostate pathology. Anal Quant Cytol Histol. 20:1998;443-460
19. Bartels P.H., Bartels H., Montironi R., et al. Machine vision in the detection of prostate lesions in histologic sections. Anal Quant Cytol Histol. 20:1998;358-364
20. Haralick R.M., Shanmugsm K., Dinstein I. Texture features for image classification. IEEE Trans Syst Man Cybern. 3:1973;610-621
21. Bartels P.H., Bartels H., Montroni R., et al. Machine vision in the detection of prostate lesions in histologic sections. Anal Quant Cytol Histol. 20:1998;358-364
22. Varma M., Lee M.W., Tamboli P., et al. Morphologic criteria for the diagnosis of prostatic adenocarcinoma in needle biopsy specimens. Arch Pathol Lab Med. 126:2002;554-561
23. Thompson D., Richards D., Bartels H., et al. Multimegapixel images in histopathology. Anal Quant Cytol Histol. 23:2001;169-177
24. Leong F.J.W.-M., McGee J.O.'D. Automated complete slide digitization A medium for simultaneous viewing by multiple pathologists. J Pathol. 195:2002;508-514