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Cervical cancer is the second most common cancer in women worldwide, and knowledge regarding its cause and pathogenesis is expanding rapidly. Persistent infection with one of about 15 genotypes of carcinogenic human papillomavirus (HPV) causes almost all cases. There are four major steps in cervical cancer development: infection of metaplastic epithelium at(More)
OBJECTIVE This study evaluates the feasibility and performance of careHPV, a novel human papillomavirus (HPV) DNA test, when used for screening women for cervical cancer in low-resource settings. METHODS AND MATERIALS Clinician-collected (cervical) and self-collected (vaginal) careHPV specimens, visual inspection with acetic acid (VIA), and Papanicolaou(More)
Colposcopy is a critical part of gynecologic practice but has documented deficiencies, including lack of correlation between the colposcopic appearance and the severity of underlying neoplasia, limited reproducibility, and difficulty in the optimal placement of colposcopically directed biopsies. In a collaborative effort to improve colposcopy, we are(More)
This work is motivated by the need for visual information extraction and management in the growing field of medical image archives. In particular the work focuses on a unique medical repository of digital cervicographic images (" Cervigrams ") collected by the National Cancer Institute (NCI) in a longitudinal multi-year study carried out in Guanacaste,(More)
Automated segmentation and classification of diagnostic markers in medical imagery are challenging tasks. Numerous algorithms for segmentation and classification based on statistical approaches of varying complexity are found in the literature. However, the design of an efficient and automated algorithm for precise classification of desired diagnostic(More)
In this paper, we propose a new method for automated detection and segmentation of different tissue types in digitized uterine cervix images using mean-shift clustering and support vector machines (SVM) classification on cluster features. We specifically target the segmentation of precancerous lesions in a NCI/NLM archive of 60,000 cervigrams. Due to large(More)
The National Cancer Institute (NCI) is collaborating with the National Library of Medicine (NLM) to create a database of digitized images of the uterine cervix for research, training, and education. The database of 100,000 images collected in NCI projects will be Web-accessible and will contain not only the digitized images, but also clinical, longitudinal(More)
The work focuses on a unique medical repository of digital cervicographic images ("Cervigrams") collected by the National Cancer Institute (NCI) in longitudinal multiyear studies. NCI, together with the National Library of Medicine (NLM), is developing a unique web-accessible database of the digitized cervix images to study the evolution of lesions related(More)
New cervical cancer prevention strategies are arising from rapidly improving insight into human papillomavirus (HPV) natural history and cervical carcinogenesis, challenging the conventional roles of cytology and colposcopically directed biopsy as the reference standards of screening and diagnosis, respectively. HPV testing has high sensitivity but mediocre(More)
The National Library of Medicine (NLM) and the National Cancer Institute (NCI) are creating a digital archive of 100,000 cervicographic images and clinical and diagnostic data obtained through two major longitudinal studies. In addition to developing tools for Web access to these data, we are conducting research in Content-Based Image Retrieval (CBIR)(More)