Segmentation of atherosclerotic carotid plaque in ultrasound video.

The degree of stenosis of the common carotid artery (CCA) but also the characteristics of the arterial wall including plaque size, composition and elasticity represent important predictors used in the assessment of the risk for future cardiovascular events. This paper proposes and evaluates an integrated system for the segmentation of atherosclerotic carotid plaque in ultrasound video of the CCA based on normalization, speckle reduction filtering (with the hybrid median filter) and parametric active contours. The algorithm is initialized in the first video frame of the cardiac cycle with human assistance and the moving atherosclerotic plaque borders are tracked and segmented in the subsequent frames. The algorithm is evaluated on 10 real CCA digitized videos from B-mode longitudinal ultrasound segments and is compared with the manual segmentations of an expert, for every 20 frames in a time span of 3-5 seconds, covering in general 2 cardiac cycles. The segmentation results are very satisfactory with a true negative fraction (TNF) of 79.3%, a true-positive fraction (TPF) of 78.12%, a false-positive fraction (FPF) of 6.7% and a false-negative fraction (FNF) of 19.6% between the ground truth and the presented plaque segmentations, a Williams index (KI) of 80.3%, an overlap index of 71.5%, a specificity of 0.88±0.09, a precision of 0.86±0.10 and an effectiveness measure of 0.77±0.09. The results show that integrated system investigated in this study could be successfully used for the automated video segmentation of the carotid plaque.

Cross-validation in fuzzy ARTMAP for large databases.

In this paper we are examining the issue of overtraining in Fuzzy ARTMAP. Over-training in Fuzzy ARTMAP manifests itself in two different ways: (a) it degrades the generalization performance of Fuzzy ARTMAP as training progresses; and (b) it creates unnecessarily large Fuzzy ARTMAP neural network architectures. In this work, we are demonstrating that overtraining happens in Fuzzy ARTMAP and we propose an old remedy for its cure: cross-validation. In our experiments, we compare the performance of Fuzzy ARTMAP that is trained (i) until the completion of training, (ii) for one epoch, and (iii) until its performance on a validation set is maximized. The experiments were performed on artificial and real databases. The conclusion derived from those experiments is that cross-validation is a useful procedure in Fuzzy ARTMAP, because it produces smaller Fuzzy ARTMAP architectures with improved generalization performance. The trade-off is that cross-validation introduces additional computational complexity in the training phase of Fuzzy ARTMAP.

Classification of noisy signals using fuzzy ARTMAP neural networks.

This paper describes an approach to classification of noisy signals using a technique based on the fuzzy ARTMAP neural network (FAMNN). The proposed method is a modification of the testing phase of the fuzzy ARTMAP that exhibits superior generalization performance compared to the generalization performance of the standard fuzzy ARTMAP in the presence of noise. An application to textured gray-scale image segmentation is presented. The superiority of the proposed modification over the standard fuzzy ARTMAP is established by a number of experiments using various texture sets, feature vectors and noise types. The texture sets include various aerial photos and also samples obtained from the Brodatz album. Furthermore, the classification performance of the standard and the modified fuzzy ARTMAP is compared for different network sizes. Classification results that illustrate the performance of the modified algorithm and the FAMNN are presented.

The intramedullary skeletal kinetic distractor (ISKD): first clinical results of a new intramedullary nail for lengthening of the femur and tibia.

In 1986, a programme was initiated by the senior author to develop a reliable, mechanically activated, intramedullary lengthening device with a non-invasive means of measuring the progress of lengthening without X-ray. We report results of design, biomechanical testing, in vivo animal testing and clinical implantation of the first 20 intramedullary skeletal kinetic distractors (ISKDs) in adult patients with limb-length discrepancies. Twenty ISKD devices were implanted in 18 patients (14 males and four females). Lengthening was required due to infection (ten), trauma (six), polio (one) and burn (one). Six femurs and 14 tibias were lengthened. Mean patient age was 40 years (range, 18-65 years). No implant related infections, non-unions, malunions or joint contractures were observed. A design change was made following two initial hardware failures, after which there were no further breakages. Average lengthening was 49 mm (range, 29-110 mm). The average lengthening rate was 0.82 mm/day (range, 1.7-0.4 mm/day). Ability to work, walk and drive before, during and after treatment with the ISKD compared favourably with that of similar patients undergoing lengthening using the 'monorail' method in our practice. The ISKD appears to be a safe and cost-effective alternative to external fixators that reduces lifestyle disruption and complications during adult limb-lengthening procedures.