MR quantification of cerebral ventricular volume using a semiautomated algorithm.
LA Johnson, JD Pearlman, CA Miller… - American journal …, 1993 - Am Soc Neuroradiology
LA Johnson, JD Pearlman, CA Miller, TI Young, KR Thulborn
American journal of neuroradiology, 1993•Am Soc NeuroradiologyPURPOSE A semiautomated border identification algorithm, insensitive to user bias, is
evaluated for accuracy and speed in the measurement of ventricular volumes from three-
dimensional MR images. METHODS A three-dimensional gradient-echo technique was
implemented on a Signa clinical imaging system. Data from phantoms and patients were
analyzed for volume using a segmentation algorithm designed with: 1) correction for partial
volume averaging; 2) insensitivity to user bias; and 3) speed. Accuracy, precision, and intra …
evaluated for accuracy and speed in the measurement of ventricular volumes from three-
dimensional MR images. METHODS A three-dimensional gradient-echo technique was
implemented on a Signa clinical imaging system. Data from phantoms and patients were
analyzed for volume using a segmentation algorithm designed with: 1) correction for partial
volume averaging; 2) insensitivity to user bias; and 3) speed. Accuracy, precision, and intra …
PURPOSE
A semiautomated border identification algorithm, insensitive to user bias, is evaluated for accuracy and speed in the measurement of ventricular volumes from three-dimensional MR images.
METHODS
A three-dimensional gradient-echo technique was implemented on a Signa clinical imaging system. Data from phantoms and patients were analyzed for volume using a segmentation algorithm designed with: 1) correction for partial volume averaging; 2) insensitivity to user bias; and 3) speed. Accuracy, precision, and intra- and interobserver variability were determined.
RESULTS
Average error for phantom studies was 4% to 6%, or 1 to 2 cc across the volumes, which ranged from normal to mild hydrocephalus (< 60 cc). Patient studies showed intra- and interobserver error of 2.3% and 7.8%, respectively. The correction for partial volume averaging resulted in a threefold decrease in error. Data were acquired and reconstructed within 7 minutes. Experienced radiologists required less than 15 minutes to perform each analysis.
CONCLUSIONS
This algorithm allows accurate measurement of ventricular volumes in an efficient, minimally supervised manner.
American Journal of Neuroradiology