Tensor Analysis and Fusion of Multimodal Brain Images

Current high-throughput data acquisition technologies probe dynamical systems with different imaging modalities, generating massive data sets at different spatial and temporal resolutions posing challenging problems in multimodal data fusion. A case in point is the attempt to parse out the brain structures and networks that underpin human cognitive processes by analysis of different neuroimaging modalities (functional MRI, EEG, NIRS etc.). We emphasize that the multimodal, multi-scale nature of neuroimaging data is well reflected by a multi-way (tensor) structure where the underlying processes can be summarized by a relatively small number of components or "atoms". We introduce Markov-Penrose diagrams - an integration of Bayesian DAG and tensor network notation in order to analyze these models. These diagrams not only clarify matrix and tensor EEG and fMRI time/frequency analysis and inverse problems, but also help understand multimodal fusion via Multiway Partial Least Squares and Coupled Matrix-Tensor Factorization. We show here, for the first time, that Granger causal analysis of brain networks is a tensor regression problem, thus allowing the atomic decomposition of brain networks. Analysis of EEG and fMRI recordings shows the potential of the methods and suggests their use in other scientific domains.Comment: 23 pages, 15 figures, submitted to Proceedings of the IEE

Deep Learning vs. Conventional Machine Learning: Pilot Study of WMH Segmentation in Brain MRI with Absence or Mild Vascular Pathology

In the wake of the use of deep learning algorithms in medical image analysis, we compared performance of deep learning algorithms, namely the deep Boltzmann machine (DBM), convolutional encoder network (CEN) and patch-wise convolutional neural network (patch-CNN), with two conventional machine learning schemes: Support vector machine (SVM) and random forest (RF), for white matter hyperintensities (WMH) segmentation on brain MRI with mild or no vascular pathology. We also compared all these approaches with a method in the Lesion Segmentation Tool public toolbox named lesion growth algorithm (LGA). We used a dataset comprised of 60 MRI data from 20 subjects in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, each scanned once every year during three consecutive years. Spatial agreement score, receiver operating characteristic and precision-recall performance curves, volume disagreement score, agreement with intra-/inter-observer reliability measurements and visual evaluation were used to find the best configuration of each learning algorithm for WMH segmentation. By using optimum threshold values for the probabilistic output from each algorithm to produce binary masks of WMH, we found that SVM and RF produced good results for medium to very large WMH burden but deep learning algorithms performed generally better than conventional ones in most evaluations

Brain findings associated with iodine deficiency identified by magnetic resonance methods: a systematic review

Objectives: Iodine deficiency (ID) is a common cause of preventable brain damage and mental retardation worldwide, according to the World Health Organisation. It may adversely affect brain maturation processes that potentially result in structural and metabolic brain abnormalities, visible on Magnetic Resonance (MR) techniques. Currently, however, there has been no review of the appearance of these brain changes on MR methods. Methods: A systematic review was conducted using 3 online search databases (Medline, Embase and Web of Knowledge) using multiple combinations of the following search terms: iodine, iodine deficiency, magnetic resonance, MRI, MRS, brain, imaging and iodine deficiency disorders (i.e. hypothyroxinaemia, congenital hypothyroidism, hypothyroidism and cretinism). Results: Up to May 2013, 1673 related papers were found. Of these, 29 studies confirmed their findings directly using MR Imaging and/or MR Spectroscopy. Of them, 28 were in humans and involved 157 subjects, 46 of whom had primary hypothyroidism, 97 had congenital hypothyroidism, 3 had endemic cretinism and 11 had subclinical hypothyroidism. The studies were small, with a mean relevant sample size of 6, median 2, range 1 - 35, while 14 studies were individual case reports. T1-weighted was the most commonly used MRI sequence (20/29 studies) and 1.5 Tesla was the most commonly used magnet strength (6/10 studies that provided this information). Pituitary abnormalities (18/29 studies) and cerebellar atrophy (3/29 studies) were the most prevalent brain abnormalities found. Only fMRI studies (3/29) reported cognition-related abnormalities but the brain changes found were limited to a visual description in all studies. Conclusions: More studies that use MR methods to identify changes on brain volume or other global structural abnormalities and explain the mechanism of ID causing thyroid dysfunction and hence cognitive damage are required. Given the role of MR techniques in cognitive studies, this review provides a starting point for researching the macroscopic structural brain changes caused by ID.</br

Confiabilidad y validez de un instrumento que mide la colaboración organizacional en una universidad pública de Huehuetoca (centro de México)

En contextos de riesgos y contingencias de los mercados, así como en los efectos de las políticas de fomento empresarial subsecuentes, la colaboración organizacional es observable en instituciones y empresas orientadas por sistemas complejos que desarrollan climas de relaciones, apoyos, innovaciones, propósitos y metas. Se llevó a cabo un estudio no experimental, trasversal y exploratorio con una selección no probabilística de 300 administrativos, académicos y estudiantes de una universidad pública. A partir de un modelo estructural se demostró la consistencia interna y la validez de constructo de la colaboración organizacional la cual fue reflejada por el factor de clima de relaciones. En relación con el estado del conocimiento se recomienda la inclusión del constructo de colaboración organizacional en los modelos de cultura laboral siempre que estos se lleven a cabo en casos específicos de desaceleración y recesión económica, crisis ecológica y responsabilidad social