Biomedical subjects

J Duryea

Publications and source records attributed to J Duryea.

14 recordsLinked to original sources

PubMed2000

Trainable rule-based algorithm for the measurement of joint space width in digital radiographic images of the knee.

The progression of osteoarthritis (OA) can be monitored by measuring the minimum joint space width (mJSW) between the edges of the femoral condyle and the tibial plateau on radiographs of the knee. This is generally performed by a trained physician using a graduated magnifying lens and is prone to the subjectivity and variation associated with observer measurement. We have developed software that performs this measurement automatically on digitized radiographs. The test data consisted of 180 digitized radiographs of the knee (90 duplicate acquisitions) from 18 normal (nonarthritic) subjects and 38 images from 10 subjects with OA. These were digitized and manually cropped so that the images were free of nonanatomical structures and the knee was approximately centered. The software first determined the edge of the femoral condyle on 400 microm pixel subsampled images. Contours marking the location of the tibial plateau in the medial compartment were found on 100 microm images using the femoral edge as a reference. The algorithm was trained using an independent but similar data set and using a jackknife approach with the test data. The results were compared to contours drawn by a trained reader and the duplicate acquisitions were used to measure the reproducibility of the mJSW measurement. The reproducibility was 0.16 mm and 0.18 mm for normal and osteoarthritic knees, respectively, representing an improvement of approximately a factor of 2 over manual measurement. The algorithm also showed excellent agreement with the hand-drawn contours and with mJSW determined by the manual method.

Algorithms↗

PubMed2000

Neural network based algorithm to quantify joint space width in joints of the hand for arthritis assessment.

Arthritis diseases are widespread with enormous societal costs. The two most common forms, rheumatoid arthritis and osteoarthritis, affect joints of the hand and cause narrowing of the joint spaces as the disease destroys the articular cartilage. Radiographic assessment is one of the most promising tools to detect subtle changes in joint space width (JSW), and therefore disease progression. Currently radiographic assessment of arthritis in joints of the hand is accomplished though semiquantitative subjective scoring systems which do not provide a quantitative measurement of the JSW. We describe here an automated method which calculates the average JSW of the metacarpophalangeal (MCP), proximal interphalangeal (PIP), and distal interphalangeal (DIP) joint spaces for fingers 2 to 5 (index, middle, ring, and little) on digitized hand radiographs. The method was tested with a set of 54 hand radiographs on joints with mild to moderate rheumatoid arthritis. Performance was evaluated by comparing algorithm measured JSW to a gold standard determined from expertly hand-drawn joint margins. The agreement was quantified by a measurement of root mean square deviation, 0.148 mm, 0.089 mm, and 0.114 mm for the MCP, PIP, and DIP joints, respectively. In addition, the algorithm measured JSW strongly correlated with the gold standard: R2=0.80 (MCP), R2= 0.82 (PIP), and R2= 0.84 (DIP). This is an accurate and robust algorithm and should provide a more quantitative measure of disease progression than current methods.

Algorithms↗

PubMed1995

Filter wheel equalization for chest radiography: a computer simulation.

A chest radiographic equalization system using lung-shaped templates mounted on filter wheels is under development. Using this technique, 25 lung templates for each lung are available on two computer controlled wheels which are located in close proximity to the x-ray tube. The large magnification factor (> 10X) of the templates assures low-frequency equalization due to the blurring of the focal spot. A low-dose image is acquired without templates using a (generic) digital receptor, the image is analyzed, and the left and right lung fields are automatically identified using software developed for this purpose. The most appropriate left and right lung templates are independently selected and are positioned into the field of view at the proper location under computer control. Once the templates are positioned, acquisition of the equalized radiographic image onto film commences at clinical exposure levels. The templates reduce the exposure to the lung fields by attenuating a fraction of the incident x-ray fluence so that the exposure to the mediastinum and diaphragm areas can be increased without overexposing the lungs. A data base of 824 digitized chest radiographs was used to determine the shape of the specific lung templates, for both left and right lung fields. A second independent data base of 208 images was used to test the performance of the templates using computer simulations. The template shape characteristics derived from the clinical image data base are demonstrated. The detected exposure in the lung fields on conventional chest radiographs was found to be, on average, three times the detected exposure behind the diaphragm and mediastinum.(ABSTRACT TRUNCATED AT 250 WORDS)

Biophysical Phenomena↗

PubMed1995

A fully automated algorithm for the segmentation of lung fields on digital chest radiographic images.

A completely automated algorithm is presented which is capable of identifying both the right- and left-lung fields on digitized chest radiographic images. The algorithm is tested on a sample of 802 chest images against lung fields drawn by a human observer. The average accuracies are found to be 0.957 +/- 0.003 and 0.960 +/- 0.003 for right- and left-lung regions, respectively. To put them into perspective, the results are compared to several other simple segmentation techniques. These include a comparison of two sets of lung fields drawn by the human observer at different times which yielded accuracies of 0.967 +/- 0.005 and 0.967 +/- 0.004 for right- and left-lung regions, respectively.

Algorithms↗

PubMed1995

Filter wheel equalization in chest radiography: demonstration with a prototype system.

PURPOSE: To determine the feasibility of using the filter wheel equalization (FWE) technique for radiographic equalization in chest radiography. MATERIALS AND METHODS: An FWE system with two rotating wheels (one for each lung) with 25 lung-shaped, 1.0-mm-thick copper templates was constructed. Preexposure images were acquired; the computer used these images to select and position templates for each lung. An equalized radiograph was then produced. Radiographs were acquired in two male volunteers (both 33 years of age) and in a phantom. RESULTS: Optical densities in the lungs and nonlung areas on a conventional phantom radiograph were 2.07 and 0.55, respectively; after equalization, the corresponding optical densities were 2.06 and 1.42. Outside the lungs, radiographic contrast (difference in optical density) increased threefold; in the lungs, there was a very small decrease in radiographic contrast due to beam hardening. Well-equalized and relatively artifact-free radiographs were obtained with a 20-msec exposure time. CONCLUSION: The FWE system was shown in the laboratory to be feasible.

Absorptiometry, Photon↗

PubMed1993