A methodology for quality control in cell nucleus segmentation

In order to achieve the very high accuracy rates required in unsupervised automated biomedical applications, it is often necessary to complement a successful segmentation algorithm with a robust error checking stage. The better the segmentation strategy, the less severe the error checking decisions need to be and the fewer correct segmentations that are discarded. These issues are dealt with in this paper in order to achieve 100% accuracy on a data set of 19946 cell nucleus images using an established segmentation scheme with a success rate of 99.47%. The method is based upon measuring changes in the final segmentation contour as the one parameter that governs its behaviour is varied. 1. Introduction remove potential artefacts based on shape and appearance that was capable of detecting some of the incorrectly segmented nuclei [9]. Nordin describes an algorithm that is able to report a failure at various levels of segmentation, as well as a separate artefact rejection stage [11]. McKenna used a neural network to preselect potential nuclei in scenes for subsequent segmentation. It was pointed out that a post-processing stage would also be necessary to filter out 'erroneously detected objects'[10]. A common trait in these techniques is the use of a separate process to view the output of the segmentation and to use shape and appearance measurements to classify the results as 'pass' (looks like a cell) or 'fail' (doesn't look like a cell). We have proposed a segmentation scheme that not only employs an algorithm with much better performance than previously reported [3], but also enables a confidence measure in the resulting segmentation to be given

Method for Accurate Unsupervised Cell Nucleus Segmentation

To achieve the extreme accuracy rates demanded by applications in unsupervised automated cytology, it is frequently necessary to supplement the primary segmentation algorithm with a segmentation quality control system. The more robust the segmentation strategy, the less severe the data pruning need be at the segmentation validation stage. These issues are addressed as we describe our cell nucleus segmentation strategy which is able to achieve 100% accurate segmentation from a data set of 19946 cell nucleus images by automatically discarding the most difficult cell images. The automatic quality checking is applied to enhance the performance of a robust energy minimisation based segmentation scheme which already achieved a 99.47% accurate segmentation rate

Bayesian Analysis of Cell Nucleus Segmentation by a Viterbi Search Based Active Contour

An image segmentation scheme is shown to be exceptionally successful through the application of high-level knowledge of the required image objects (cell nuclei). By tuning the algorithm's single parameter, it is shown that the performance can be maximised for the dataset, but leads to individual failures that may require alternative choices. A second stage is introduced to process each of the resulting segmentations obtained by varying the parameter over the working range. This stage gives a Bayesian interpretation of the results which indicates the probable accuracy of each of the segmentations that can then be used to make a decision upon whether to accept or reject the segmentation

A One-Pass Extended Depth of Field Algorithm Based on the Over-Complete Discrete Wavelet Transform

In this paper we describe an algorithm for extended depth of field (EDF) imaging based on the over-complete discrete wavelet transform (OCDWT). We extend previous approaches by describing a, potentially real-time, algorithm that produces the EDF image after a single pass through the "stack" of focal plane images. In addition, we specifically study the effect of over-sampling on EDF reconstruction accuracy and show that a small degree of over-sampling considerably improves the quality of the EDF image

Registration evaluation of dynamic breast MR images

The interpretation of dynamic contrast-enhanced breast MR images is predicated on the assumption of minimal voxel movement during the time course of the image acquisition. Misalignment of the dynamic image sequence as a result of movement during image acquisition can lead to potentially misleading diagnostic conclusions. In this paper a new methodology is presented for assessing the degree of in-plane (intra-slice) movement in a dynamic image sequence. The method is demonstrated on data from six subjects. The conclusion is that the method makes it possible to quantitatively qualify the accuracy of computed enhancement curves and more importantly to identify unacceptably poor registration

Time to Switch to Second-line Antiretroviral Therapy in Children With Human Immunodeficiency Virus in Europe and Thailand.

Background: Data on durability of first-line antiretroviral therapy (ART) in children with human immunodeficiency virus (HIV) are limited. We assessed time to switch to second-line therapy in 16 European countries and Thailand. Methods: Children aged <18 years initiating combination ART (≥2 nucleoside reverse transcriptase inhibitors [NRTIs] plus nonnucleoside reverse transcriptase inhibitor [NNRTI] or boosted protease inhibitor [PI]) were included. Switch to second-line was defined as (i) change across drug class (PI to NNRTI or vice versa) or within PI class plus change of ≥1 NRTI; (ii) change from single to dual PI; or (iii) addition of a new drug class. Cumulative incidence of switch was calculated with death and loss to follow-up as competing risks. Results: Of 3668 children included, median age at ART initiation was 6.1 (interquartile range (IQR), 1.7-10.5) years. Initial regimens were 32% PI based, 34% nevirapine (NVP) based, and 33% efavirenz based. Median duration of follow-up was 5.4 (IQR, 2.9-8.3) years. Cumulative incidence of switch at 5 years was 21% (95% confidence interval, 20%-23%), with significant regional variations. Median time to switch was 30 (IQR, 16-58) months; two-thirds of switches were related to treatment failure. In multivariable analysis, older age, severe immunosuppression and higher viral load (VL) at ART start, and NVP-based initial regimens were associated with increased risk of switch. Conclusions: One in 5 children switched to a second-line regimen by 5 years of ART, with two-thirds failure related. Advanced HIV, older age, and NVP-based regimens were associated with increased risk of switch