Congenital heart disease is the leading cause of birth defect related deaths. The modified myocardial performance index of the right ventricle (R-MPI) is a sensitive and early clinical indicator of fetal cardiac health. Objective repeatable measurement of R-MPI is an important deciding factor for the clinical adaptation of the R-MPI. In this work, we describe a novel method for automatic computation of R-MPI from the Pulsed Wave Doppler (PWD) images. Our method involves a Fourier series based cardiac cycle detection followed by an adaptive windowed energy based valve click localization and weighted gradient based refinement. Using this method, we have been able to measure R-MPI reliably with a mean difference of 0.0075 ± 0.034 from 170 expert annotations on 68 fetal PWD images with an Intra-Class Correlation (ICC) of 0.9380. Furthermore, we have introduced novel methods for normalization and synchronization of PWD images acquired at two different time intervals for the assessment of iso-volume time intervals and an accurate measurement of R-MPI.
Follicle quantification refers to the computation of the number and size of follicles in 3D ultrasound volumes of the
ovary. This is one of the key factors in determining hormonal dosage during female infertility treatments. In this paper,
we propose an automated algorithm to detect and segment follicles in 3D ultrasound volumes of the ovary for
quantification. In a first of its kind attempt, we employ noise-robust phase symmetry feature maps as likelihood function
to perform mean-shift based follicle center detection. Max-flow algorithm is used for segmentation and gray weighted
distance transform is employed for post-processing the results. We have obtained state-of-the-art results with a true
positive detection rate of >90% on 26 3D volumes with 323 follicles.