Search results for " Automated"
showing 10 items of 130 documents
Non-negative blind source separation techniques for tumor tissue typing using HR-MAS signals.
2010
Given High Resolution Magic Angle Spinning (HR-MAS) signals from several glioblastoma tumor subjects, the goal is to differentiate between tumor tissue types by separating the different sources that contribute to the profile of each spectrum. Blind source separation techniques are applied for obtaining characteristic profiles for necrosis, high cellular tumor and border tumor tissue, and providing the contribution (abundance) of each tumor tissue to the profile of the spectra. The problem is formulated as a non-negative source separation problem. We illustrate the effectiveness of the proposed methods and we analyze to which extent the dimension of the input space could influence the perfor…
Ranking Series of Cancer-Related Gene Expression Data by Means of the Superposing Significant Interaction Rules Method
2020
The Superposing Significant Interaction Rules (SSIR) method is a combinatorial procedure that deals with symbolic descriptors of samples. It is able to rank the series of samples when those items are classified into two classes. The method selects preferential descriptors and, with them, generates rules that make up the rank by means of a simple voting procedure. Here, two application examples are provided. In both cases, binary or multilevel strings encoding gene expressions are considered as descriptors. It is shown how the SSIR procedure is useful for ranking the series of patient transcription data to diagnose two types of cancer (leukemia and prostate cancer) obtaining Area Under Recei…
Workflow-centred open-source fully automated lung volumetry in chest CT
2019
Aim To develop a robust open-source method for fully automated extraction of total lung capacity (TLC) from computed tomography (CT) images and to demonstrate its integration into the clinical workflow. Materials and methods Using only open-source software, an algorithm was developed based on a region-growing method that does not require manual interaction. Lung volumes calculated from reconstructions with different kernels (TLCCT) were assessed. To validate the algorithm calculations, the results were correlated to TLC measured by pulmonary function testing (TLCPFT) in a subgroup of patients for which this information was available within 3 days of the CT examination. Results A total of 28…
A supervised learning framework of statistical shape and probability priors for automatic prostate segmentation in ultrasound images
2013
Prostate segmentation aids in prostate volume estimation, multi-modal image registration, and to create patient specific anatomical models for surgical planning and image guided biopsies. However, manual segmentation is time consuming and suffers from inter-and intra-observer variabilities. Low contrast images of trans rectal ultrasound and presence of imaging artifacts like speckle, micro-calcifications, and shadow regions hinder computer aided automatic or semi-automatic prostate segmentation. In this paper, we propose a prostate segmentation approach based on building multiple mean parametric models derived from principal component analysis of shape and posterior probabilities in a multi…
Training labels for hippocampal segmentation based on the EADC-ADNI harmonized hippocampal protocol
2015
Abstract Background The European Alzheimer's Disease Consortium and Alzheimer's Disease Neuroimaging Initiative (ADNI) Harmonized Protocol (HarP) is a Delphi definition of manual hippocampal segmentation from magnetic resonance imaging (MRI) that can be used as the standard of truth to train new tracers, and to validate automated segmentation algorithms. Training requires large and representative data sets of segmented hippocampi. This work aims to produce a set of HarP labels for the proper training and certification of tracers and algorithms. Methods Sixty-eight 1.5 T and 67 3 T volumetric structural ADNI scans from different subjects, balanced by age, medial temporal atrophy, and scanner…
Irregularity of the posterior corneal surface after curved interface femtosecond laser-assisted versus microkeratome-assisted descemet stripping auto…
2013
During donor tissue preparation for Descemet stripping automated endothelial keratoplasty (DSAEK), either microkeratome or femtosecond laser can be used for intrastromal cutting. We compared morphological and functional outcomes after DSAEK using both cutting techniques.In this retrospective study, 22 uneventful DSAEK surgeries were reviewed. Eight donor corneas were prepared for DSAEK using the VisuMax femtosecond laser (Carl Zeiss Meditec AG, Jena, Germany). Fourteen corneas were processed using an Amadeus II microkeratome (Ziemer Ophthalmic Systems AG, Port, Switzerland). The postoperative best spectacle-corrected visual acuity was measured. Furthermore, corneal optical coherence tomogra…
Dysfunction of attention switching networks in amyotrophic lateral sclerosis
2019
Objective To localise and characterise changes in cognitive networks in Amyotrophic Lateral Sclerosis (ALS) using source analysis of mismatch negativity (MMN) waveforms. Rationale The MMN waveform has an increased average delay in ALS. MMN has been attributed to change detection and involuntary attention switching. This therefore indicates pathological impairment of the neural network components which generate these functions. Source localisation can mitigate the poor spatial resolution of sensor-level EEG analysis by associating the sensor-level signals to the contributing brain sources. The functional activity in each generating source can therefore be individually measured and investigat…
Facial patterns in Cercopithecoidea and Hominoidea: a geometric approach.
2006
The maxillofacial and orbital compartments of the primate skull contribute to the ontogenetic and phylogenetic variability of the viscerocranium and are of crucial evolutionary relevance. As the form of organisms changes depending on endo- and exogenous factors, metrical evaluation of specific adaptations and incorporation of the results into a biological framework could be helpful in identifying valid characters for separation of taxa (e.g. family, genus, and species) and in understanding divergence and convergence. During the last two decades a morphometric "revolution" heralded by Rohlf & Marcus (1993), Adams et al. (2004) and Oxnard (2004) brought about a synthesis of traditional quanti…
Spectral clustering of shape and probability prior models for automatic prostate segmentation.
2013
Imaging artifacts in Transrectal Ultrasound (TRUS) images and inter-patient variations in prostate shape and size challenge computer-aided automatic or semi-automatic segmentation of the prostate. In this paper, we propose to use multiple mean parametric models derived from principal component analysis (PCA) of shape and posterior probability information to segment the prostate. In contrast to traditional statistical models of shape and intensity priors, we use posterior probability of the prostate region determined from random forest classification to build, initialize and propagate our model. Multiple mean models derived from spectral clustering of combined shape and appearance parameters…
A spline-based non-linear diffeomorphism for multimodal prostate registration.
2012
This paper presents a novel method for non-rigid registration of transrectal ultrasound and magnetic resonance prostate images based on a non-linear regularized framework of point correspondences obtained from a statistical measure of shape-contexts. The segmented prostate shapes are represented by shape-contexts and the Bhattacharyya distance between the shape representations is used to find the point correspondences between the 2D fixed and moving images. The registration method involves parametric estimation of the non-linear diffeomorphism between the multimodal images and has its basis in solving a set of non-linear equations of thin-plate splines. The solution is obtained as the least…