Alzheimer Disease Detection Techniques and Methods: A Review

Brain pathological changes linked with Alzheimer's disease (AD) can be measured with Neuroimaging. In the past few years, these measures are rapidly integrated into the signatures of Alzheimer disease (AD) with the help of classification frameworks which are offering tools for diagnosis and prognosis. Here is the review study of Alzheimer's disease based on Neuroimaging and cognitive impairment classification. This work is a systematic review for the published work in the field of AD especially the computer-aided diagnosis. The imaging modalities include 1) Magnetic resonance imaging (MRI) 2) Functional MRI (fMRI) 3) Diffusion tensor imaging 4) Positron emission tomography (PET) and 5) amyloid-PET. The study revealed that the classification criterion based on the features shows promising results to diagnose the disease and helps in clinical progression. The most widely used machine learning classifiers for AD diagnosis include Support Vector Machine, Bayesian Classifiers, Linear Discriminant Analysis, and K-Nearest Neighbor along with Deep learning. The study revealed that the deep learning techniques and support vector machine give higher accuracies in the identification of Alzheimer’s disease. The possible challenges along with future directions are also discussed in the paper

Proceedings of the First International Workshop on Mathematical Foundations of Computational Anatomy (MFCA'06) - Geometrical and Statistical Methods for Modelling Biological Shape Variability

International audienceNon-linear registration and shape analysis are well developed research topic in the medical image analysis community. There is nowadays a growing number of methods that can faithfully deal with the underlying biomechanical behaviour of intra-subject shape deformations. However, it is more difficult to relate the anatomical shape of different subjects. The goal of computational anatomy is to analyse and to statistically model this specific type of geometrical information. In the absence of any justified physical model, a natural attitude is to explore very general mathematical methods, for instance diffeomorphisms. However, working with such infinite dimensional space raises some deep computational and mathematical problems. In particular, one of the key problem is to do statistics. Likewise, modelling the variability of surfaces leads to rely on shape spaces that are much more complex than for curves. To cope with these, different methodological and computational frameworks have been proposed. The goal of the workshop was to foster interactions between researchers investigating the combination of geometry and statistics for modelling biological shape variability from image and surfaces. A special emphasis was put on theoretical developments, applications and results being welcomed as illustrations. Contributions were solicited in the following areas: * Riemannian and group theoretical methods on non-linear transformation spaces * Advanced statistics on deformations and shapes * Metrics for computational anatomy * Geometry and statistics of surfaces 26 submissions of very high quality were recieved and were reviewed by two members of the programm committee. 12 papers were finally selected for oral presentations and 8 for poster presentations. 16 of these papers are published in these proceedings, and 4 papers are published in the proceedings of MICCAI'06 (for copyright reasons, only extended abstracts are provided here)

Proceedings of the Fourth International Workshop on Mathematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Biological Shape Variability Modeling (MFCA 2013), Nagoya, Japan

International audienceComputational anatomy is an emerging discipline at the interface of geometry, statistics and image analysis which aims at modeling and analyzing the biological shape of tissues and organs. The goal is to estimate representative organ anatomies across diseases, populations, species or ages, to model the organ development across time (growth or aging), to establish their variability, and to correlate this variability information with other functional, genetic or structural information. The Mathematical Foundations of Computational Anatomy (MFCA) workshop aims at fostering the interactions between the mathematical community around shapes and the MICCAI community in view of computational anatomy applications. It targets more particularly researchers investigating the combination of statistical and geometrical aspects in the modeling of the variability of biological shapes. The workshop is a forum for the exchange of the theoretical ideas and aims at being a source of inspiration for new methodological developments in computational anatomy. A special emphasis is put on theoretical developments, applications and results being welcomed as illustrations. Following the first edition of this workshop in 2006, second edition in New-York in 2008, the third edition in Toronto in 2011, the forth edition was held in Nagoya Japan on September 22 2013

2014 IMSAloquium, Student Investigation Showcase

The ability to work with professionals is a life-changing experience for our students. Working with world-class scholars and advisors, students have contributed to advances in a variety of fields from science, technology, engineering and mathematics, to the performing arts and history.https://digitalcommons.imsa.edu/archives_sir/1006/thumbnail.jp

05. 2014 IMSAloquium Student Investigation Showcase

https://digitalcommons.imsa.edu/class_of_2015/1003/thumbnail.jp

Análisis anatomorradiológico del sistema límbico con diferentes técnicas de imagen

[ES] El Sistema Límbico (SL) está constituido por un conjunto de estructuras cerebrales ubicadas en la línea media rodeando al cuerpo calloso e interconectadas entre sí por conexiones aferentes y eferentes. Está relacionado con las emociones, la conducta, el pensamiento y la interpretación del mundo que nos rodea. Es el encargado de las respuestas viscerales ante estímulos externos: lucha, ira, huida, respuestas sexuales, sentimientos, memorias. A lo largo de la historia los diferentes componentes del SL han sido bien estudiados en preparados anatómicos, pero en las últimas décadas y debido a la aparición, desarrollo e importantes avances en las técnicas de imagen, especialmente en la RM, se ha reavivado el interés por estás estructuras cerebrales así como por las conexiones existentes entre las mismas. Las técnicas de imagen suponen pues un pilar fundamental en el estudio tanto de la anatomía como de los distintos procesos patológicos del SL, siendo necesario en este último caso una adecuada correlación clínicoradiológica, asumiendo la prueba de imagen como un método complementario en un contexto clínico determinado. Es, por lo tanto, fundamental el adecuado conocimiento anatómico para una correcta interpretación de los hallazgos de cara a la toma de decisiones en el campo clínico. Entre las diferentes técnicas de imagen para el estudio del SL se dispone de la EG en el caso del recién nacido y de la RM en el adulto, obteniéndose mediante esta última técnica imágenes multiplanares, reconstrucciones 3D, estudios vasculares y estudios tractográficos. El gran peso de las diferentes técnicas de imagen, en el día a día de la práctica clínica, junto con la gran demanda y alto nivel de exigencia diagnóstica nos obliga tanto a un exhaustivo conocimiento de la anatomía como a un adecuado manejo en el tratamiento de las imágenes mediante las distintas aplicaciones informáticas de las que disponemos. Es de suponer que en un futuro no muy lejano asistiremos a nuevos avances en el campo del diagnóstico por imagen, lo que nos facilitará aún más, tanto el estudio anatómico como la comprensión de las distintas patologías

Auditory comprehension: from the voice up to the single word level

Auditory comprehension, the ability to understand spoken language, consists of a number of different auditory processing skills. In the five studies presented in this thesis I investigated both intact and impaired auditory comprehension at different levels: voice versus phoneme perception, as well as single word auditory comprehension in terms of phonemic and semantic content. In the first study, using sounds from different continua of ‘male’-/pæ/ to ‘female’-/tæ/ and ‘male’-/tæ/ to ‘female’-/pæ/, healthy participants (n=18) showed that phonemes are categorised faster than voice, in contradistinction with the common hypothesis that voice information is stripped away (or normalised) to access phonemic content. Furthermore, reverse correlation analysis suggests that gender and phoneme are processed on the basis of different perceptual representations. A follow-up study (same paradigm) in stroke patients (n=25, right or left hemispheric brain lesions, both with and without aphasia) showed that lesions of the right frontal cortex (likely ventral inferior frontal gyrus) leads to systematic voice perception deficits while left hemispheric lesions can elicit both voice and phoneme deficits. Together these results show that phoneme processing is lateralized while voice information processing requires both hemispheres. Furthermore, this suggests that commencing Speech and Language Therapy at a low level of acoustic processing/voice perception may be an appropriate method in the treatment of phoneme perception impairments. A longitudinal case study (CF) of crossed aphasia (rare acquired communication impairment secondary to lesion ipsilateral to the dominant hand) is then presented alongside a mini-review of the literature. Extensive clinical investigation showed that CF presented with word-finding difficulties related to impaired auditory phonological analysis, while functional Magnetic Resonance Imaging (fMRI) analyses showed right hemispheric lateralization of language functions (reading, repetition and verb generation). These results, together with the co-morbidity analysis from the mini-review, suggest that crossed aphasia can be explained by developmental disorders which cause partial right lateralization shift of language processes. Interestingly, in CF this process did not affect voice lateralization and information processing, suggesting partial segregation of voice and speech processing. In the last two studies, auditory comprehension was examined at the single word level using a word-picture matching task with congruent (correct target) and incongruent (semantic, phonological and unrelated foils) conditions. fMRI in healthy participants (n=16) revealed a key role of the pars triangularis (phonological processing), the left angular gyrus (semantic incongruency) and the left precuneus (semantic relatedness) in this task – regions typically associated via the arcuate fasciculus and often impaired in aphasia. Further investigation of stroke patients on the same task (n=15) suggested that the connections between the angular gyrus and the pars triangularis serve a fundamental role in semantic processing. The quality of a published word-picture matching task was also investigated, with results questioning the clinical relevance of this task as an assessment tool. Finally, a pilot study looking at the effect of a computer-assisted auditory comprehension therapy (React2©) in 6 stroke patients (vs. 6 healthy controls and 6 stroke patients without therapy) is presented. Results show that the more therapy patients carry out the more improvement is seen in the semantic processing of single nouns. However, these results need to be reproduced on a larger scale in order to generalise any outcomes. Overall, the findings from these studies present new insight into, as well as extending on, current cognitive and neuroanatomical models of voice perception, speech perception and single word auditory comprehension. A combinatorial approach to cognitive and neuroanatomical models is proposed in order to further research, and thus improve clinical care, into impaired auditory comprehension

Object Recognition

Vision-based object recognition tasks are very familiar in our everyday activities, such as driving our car in the correct lane. We do these tasks effortlessly in real-time. In the last decades, with the advancement of computer technology, researchers and application developers are trying to mimic the human's capability of visually recognising. Such capability will allow machine to free human from boring or dangerous jobs