Add to ORKGThis work is motivated by the need for visual information management in the growing field of digital libraries and by the increasing information retrieval demands in the domains of medical imaging and telemedicine. We focus on a large database of digitized 35mm slides of the uterine cervix collected by the National Cancer Institute (NCI), National Institutes of Health (NIH), to study the evolution of lesions related to cervical cancer. As a first step towards this goal we focus on the problem of intelligently labeling (segmenting) regions of medical interest within the cervigram image. In this paper we use statistical tools for the segmentation of three tissue types of interest. 1
In prior research, the authors introduced an automated, localized, fusion-based approach for classif...
We have the goal of developing computer algorithms for indexing a collection of digitized x-ray imag...
Cervical cancer, the second most common cancer affecting women worldwide and the most common in deve...
The National Cancer Institute has collected a large database of digitized 35mm slides of the uterine...
Content-based indexing and retrieval is gaining increasing interest in the medical domain with the g...
In this work we focus on the generation of reliable ground truth data for a large medical repository...
Cervical cancer is the second most common type of cancer that prevails among women. The death rate d...
The National Cancer Institute has collected a large database of uterine cervix images, termed “cervi...
This paper presents work toward indexing the image content in a collection of 17,000 cervical spine ...
Abstract—This paper presents a procedure for automatic extraction and segmentation of a class-specif...
In a developed country like United States, cervical cancer rate has been improved by 70% in the last...
We propose and verify a method for color-based clus-ter segmentation of the various tissues from ect...
Cervical cancer is the third most common cancer in women worldwide and the leading cause of cancer d...
The region of interest (RoI) identification has a significant potential for yielding information abo...
In the past decades the number of medical images inspected daily in health centers, as well as the c...
In prior research, the authors introduced an automated, localized, fusion-based approach for classif...
We have the goal of developing computer algorithms for indexing a collection of digitized x-ray imag...
Cervical cancer, the second most common cancer affecting women worldwide and the most common in deve...
The National Cancer Institute has collected a large database of digitized 35mm slides of the uterine...
Content-based indexing and retrieval is gaining increasing interest in the medical domain with the g...
In this work we focus on the generation of reliable ground truth data for a large medical repository...
Cervical cancer is the second most common type of cancer that prevails among women. The death rate d...
The National Cancer Institute has collected a large database of uterine cervix images, termed “cervi...
This paper presents work toward indexing the image content in a collection of 17,000 cervical spine ...
Abstract—This paper presents a procedure for automatic extraction and segmentation of a class-specif...
In a developed country like United States, cervical cancer rate has been improved by 70% in the last...
We propose and verify a method for color-based clus-ter segmentation of the various tissues from ect...
Cervical cancer is the third most common cancer in women worldwide and the leading cause of cancer d...
The region of interest (RoI) identification has a significant potential for yielding information abo...
In the past decades the number of medical images inspected daily in health centers, as well as the c...
In prior research, the authors introduced an automated, localized, fusion-based approach for classif...
We have the goal of developing computer algorithms for indexing a collection of digitized x-ray imag...
Cervical cancer, the second most common cancer affecting women worldwide and the most common in deve...