Výsledky vyhledávání - "DSouza, Adora M."

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Large-scale nonlinear Granger causality: A data-driven, multivariate approach to recovering directed networks from short time-series data

Autor: Wismüller, Axel, DSouza, Adora M., Abidin, Anas Z.

To gain insight into complex systems it is a key challenge to infer nonlinear causal directional relations from observational time-series data. Specifically, estimating causal relationships between interacting components in large systems with only sh

Externí odkaz: http://arxiv.org/abs/2009.04681

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Automated Identification of Thoracic Pathology from Chest Radiographs with Enhanced Training Pipeline

Autor: DSouza, Adora M., Abidin, Anas Z., Wismüller, Axel

Publikováno v: Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, vol. 10950, p. 109503F, (2019)

Chest x-rays are the most common radiology studies for diagnosing lung and heart disease. Hence, a system for automated pre-reporting of pathologic findings on chest x-rays would greatly enhance radiologists' productivity. To this end, we investigate

Externí odkaz: http://arxiv.org/abs/2006.06805

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MRI Tumor Segmentation with Densely Connected 3D CNN

Autor: Chen, Lele, Wu, Yue, DSouza, Adora M., Abidin, Anas Z., Wismuller, Axel, Xu, Chenliang

Glioma is one of the most common and aggressive types of primary brain tumors. The accurate segmentation of subcortical brain structures is crucial to the study of gliomas in that it helps the monitoring of the progression of gliomas and aids the eva

Externí odkaz: http://arxiv.org/abs/1802.02427

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A Framework for Exploring Non-Linear Functional Connectivity and Causality in the Human Brain: Mutual Connectivity Analysis (MCA) of Resting-State Functional MRI with Convergent Cross-Mapping and Non-Metric Clustering

Autor: Wismüller, Axel, Wang, Xixi, DSouza, Adora M., Nagarajan, Mahesh B.

We present a computational framework for analysis and visualization of non-linear functional connectivity in the human brain from resting state functional MRI (fMRI) data for purposes of recovering the underlying network community structure and explo

Externí odkaz: http://arxiv.org/abs/1407.3809

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