Development of Computer-aided Detection and Diagnosis From Imaging Techniques
| Status: | Enrolling by invitation |
|---|---|
| Conditions: | Cancer, Cancer |
| Therapuetic Areas: | Oncology |
| Healthy: | No |
| Age Range: | Any |
| Updated: | 3/22/2019 |
| Start Date: | March 20, 2003 |
Development and Evaluation of Techniques for Computer Aided Detection and Diagnosis From Radiologic Images
This study will develop and evaluate new techniques for computer-aided detection and
diagnosis (CAD) of medical problems using images from diagnostic tests such as computed
tomography (CT), ultrasound, nuclear medicine and x-ray images. The Food and Drug
Administration has approved CAD techniques for detecting masses and calcifications on
mammography and lung nodules using chest x-rays. Many other applications of CAD would
potentially benefit patients. This study will explore additional uses of CAD.
The study will use imaging data, demographic information, and other medical information from
the medical charts of Clinical Center patients to test and evaluate new CAD applications.
Such applications include detection of subcutaneous (under the skin) lesions in melanoma
patients, bone lesions in patients with advanced cancer, and pulmonary emboli (blood clot
lodged in a lung artery) in patients who are known to have pulmonary emboli, and other uses.
diagnosis (CAD) of medical problems using images from diagnostic tests such as computed
tomography (CT), ultrasound, nuclear medicine and x-ray images. The Food and Drug
Administration has approved CAD techniques for detecting masses and calcifications on
mammography and lung nodules using chest x-rays. Many other applications of CAD would
potentially benefit patients. This study will explore additional uses of CAD.
The study will use imaging data, demographic information, and other medical information from
the medical charts of Clinical Center patients to test and evaluate new CAD applications.
Such applications include detection of subcutaneous (under the skin) lesions in melanoma
patients, bone lesions in patients with advanced cancer, and pulmonary emboli (blood clot
lodged in a lung artery) in patients who are known to have pulmonary emboli, and other uses.
Radiologic images are becoming more and more complex, and utilization of radiologic
techniques is accelerating. Radiologists and other clinicians are being inundated with
radiologic data. Computer aided detection and diagnosis (CAD) have the potential to improve
patient care by increasing sensitivity of diagnostic tests, reducing false positives and
improving physician efficiency. Computer aided detection and diagnosis have been under
development for many years yet there is still much work to be done to move it from the bench
to the bedside. The purpose of this project is to develop and evaluate techniques for CAD
using the existing radiologic data available in the Clinical Center's Department of
Diagnostic Radiology. Such techniques include but are not limited to automated detection of
melanoma, bone metastases and pulmonary emboli. The outcome of this study will be algorithms
and software that accurately detect lesions on radiologic studies.
techniques is accelerating. Radiologists and other clinicians are being inundated with
radiologic data. Computer aided detection and diagnosis (CAD) have the potential to improve
patient care by increasing sensitivity of diagnostic tests, reducing false positives and
improving physician efficiency. Computer aided detection and diagnosis have been under
development for many years yet there is still much work to be done to move it from the bench
to the bedside. The purpose of this project is to develop and evaluate techniques for CAD
using the existing radiologic data available in the Clinical Center's Department of
Diagnostic Radiology. Such techniques include but are not limited to automated detection of
melanoma, bone metastases and pulmonary emboli. The outcome of this study will be algorithms
and software that accurately detect lesions on radiologic studies.
- INCLUSION CRITERIA:
Inclusion criteria are the availability of radiologic examinations in the clinical PACS
(picture archiving system) in the Clinical Center. Existing Patient scans with and without
the target lesion will be included. Examples of target lesions include subcutaneous and
bone lesions and pulmonary emboli, although patient scans with other disorders depicted on
radiologic studies may be included when appropriate. Patient scans without the target
lesion may be included to determine the specificity of the computer aided detection or
diagnosis algorithm.
EXCLUSION CRITERIA:
There are no exclusion criteria.
We found this trial at
1
site
9000 Rockville Pike
Bethesda, Maryland 20892
Bethesda, Maryland 20892
Click here to add this to my saved trials
