Papers by SAMIR CHOWDHURY
Characterizing large-scale dynamic organization of the brain relies on both data-driven and mecha... more Characterizing large-scale dynamic organization of the brain relies on both data-driven and mechanistic modeling, which demands a low vs. high level of prior knowledge and assumptions about how constituents of the brain interact. However, the conceptual translation between the two is not straightforward. The present work aims to provide a bridge between data-driven and mechanistic modeling. We conceptualize brain dynamics as a complex landscape that is continuously modulated by internal and external changes. The modulation can induce transitions between one stable brain state (attractor) to another. Here, we provide a novel method – Temporal Mapper – built upon established tools from the field of Topological Data Analysis to retrieve the network of attractor transitions from time-series data alone. For theoretical validation, we use a biophysical network model to induce transitions in a controlled manner, which provides simulated time series equipped with a ground-truth attractor tr...
Low-Dose Molecular Breast Imaging for Women with Radiographically Dense Breast Tissue
Poster: "ECR 2011 / C-1898 / Low-Dose Molecular Breast Imaging for Women with Radiographical... more Poster: "ECR 2011 / C-1898 / Low-Dose Molecular Breast Imaging for Women with Radiographically Dense Breast Tissue" by: "D. J. Wagenaar1, J. W. Hugg1, R. A. Moats2, S. Chowdhury1, B. E. Patt1; 1Northridge, CA/US, 2Los Angeles, CA/US"
Network Neuroscience, 2022
For better translational outcomes, researchers and clinicians alike demand novel tools to distill... more For better translational outcomes, researchers and clinicians alike demand novel tools to distill complex neuroimaging data into simple yet behaviorally relevant representations at the single-participant level. Recently, the Mapper approach from topological data analysis (TDA) has been successfully applied on noninvasive human neuroimaging data to characterize the entire dynamical landscape of whole-brain configurations at the individual level without requiring any spatiotemporal averaging at the outset. Despite promising results, initial applications of Mapper to neuroimaging data were constrained by (1) the need for dimensionality reduction and (2) lack of a biologically grounded heuristic for efficiently exploring the vast parameter space. Here, we present a novel computational framework for Mapper—designed specifically for neuroimaging data—that removes limitations and reduces computational costs associated with dimensionality reduction and parameter exploration. We also introdu...
Applied Network Science, 2022
Path homology is a powerful method for attaching algebraic invariants to digraphs. While there ha... more Path homology is a powerful method for attaching algebraic invariants to digraphs. While there have been growing theoretical developments on the algebro-topological framework surrounding path homology, bona fide applications to the study of complex networks have remained stagnant. We address this gap by presenting an algorithm for path homology that combines efficient pruning and indexing techniques and using it to topologically analyze a variety of real-world complex temporal networks. A crucial step in our analysis is the complete characterization of path homologies of certain families of small digraphs that appear as subgraphs in these complex networks. These families include all digraphs, directed acyclic graphs, and undirected graphs up to certain numbers of vertices, as well as some specially constructed cases. Using information from this analysis, we identify small digraphs contributing to path homology in dimension two for three temporal networks in an aggregated representat...
2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA), 2019
We provide a characterization of two types of directed homology for fully-connected, feedforward ... more We provide a characterization of two types of directed homology for fully-connected, feedforward neural network architectures. These exact characterizations of the directed homology structure of a neural network architecture are the first of their kind. We show that the directed flag homology of deep networks reduces to computing the simplicial homology of the underlying undirected graph, which is explicitly given by Euler characteristic computations. We also show that the path homology of these networks is non-trivial in higher dimensions and depends on the number and size of the layers within the network. These results provide a foundation for investigating homological differences between neural network architectures and their realized structure as implied by their parameters.
Complex Networks & Their Applications IX, 2021
We present an algorithm to compute path homology for simple digraphs, and use it to topologically... more We present an algorithm to compute path homology for simple digraphs, and use it to topologically analyze various small digraphs en route to an analysis of complex temporal networks which exhibit such digraphs as underlying motifs. The digraphs analyzed include all digraphs, directed acyclic graphs, and undirected graphs up to certain numbers of vertices, as well as some specially constructed cases. Using information from this analysis, we identify small digraphs contributing to path homology in dimension 2 for three temporal networks, and relate these digraphs to network behavior. We conclude that path homology can provide insight into temporal network structure and vice versa.
Registered collimator device for nuclear imaging camera and method of forming the same
Tungsten polymer collimator for medical imaging
Quantitative radiation detection using Geiger mode avalanche photodiode binary detector cell arrays
Strip photon counting detector for nuclear medicine
Carbon-based photodiode detector for nuclear medicine
Low noise, long integration time acquisition for radiation detectors
Multi-pinhole collimation for nuclear medical imaging
Nuclear imaging system using scintillation bar detectors and method for event position calculation using the same
Modeling spectral distortions in energy resolved photon-counting x-ray detector
IEEE Nuclear Science Symposuim & Medical Imaging Conference, 2010
Abstract Conventional x-ray detectors integrate the photon energy flux, losing individual photon ... more Abstract Conventional x-ray detectors integrate the photon energy flux, losing individual photon energy information. By contrast, energy resolved photon-counting x-ray detectors (PCXDs) count photons in energy windows, thus retaining some energy information. This ...
Advantages of semiconductor CZT for medical imaging
SPIE Proceedings, 2007
Cadmium zinc telluride (CdZnTe, or CZT) is a room-temperature semiconductor radiation detector th... more Cadmium zinc telluride (CdZnTe, or CZT) is a room-temperature semiconductor radiation detector that has been developed in recent years for a variety of applications. CZT has been investigated for many potential uses in medical imaging, especially in the field of single ...
<title>Dose reduction in molecular breast imaging</title>
Medical Applications of Radiation Detectors, 2011
ABSTRACT Molecular Breast Imaging (MBI) is the imaging of radiolabeled drugs, cells, or nanoparti... more ABSTRACT Molecular Breast Imaging (MBI) is the imaging of radiolabeled drugs, cells, or nanoparticles for breast cancer detection, diagnosis, and treatment. Screening of broad populations of women for breast cancer with mammography has been augmented by the emergence of breast MRI in screening of women at high risk for breast cancer. Screening MBI may benefit the sub-population of women with dense breast tissue that obscures small tumors in mammography. Dedicated breast imaging equipment is necessary to enable detection of early-stage tumors less than 1 cm in size. Recent progress in the development of these instruments is reviewed. Pixellated CZT for single photon MBI imaging of 99mTc-sestamibi gives high detection sensitivity for early-stage tumors. The use of registered collimators in a near-field geometry gives significantly higher detection efficiency - a factor of 3.6-, which translates into an equivalent dose reduction factor given the same acquisition time. The radiation dose in the current MBI procedure has been reduced to the level of a four-view digital mammography study. In addition to screening of selected sub-populations, reduced MBI dose allows for dual-isotope, treatment planning, and repeated therapy assessment studies in the era of molecular medicine guided by quantitative molecular imaging.
Investigation on a bar detector with 3D position decoding scheme
IEEE Symposium Conference Record Nuclear Science 2004.
Abstract Simulation studies were performed to find optimum design parameters for a bar detector a... more Abstract Simulation studies were performed to find optimum design parameters for a bar detector allowing 3D position decoding of impinging gamma rays. This design incorporates surface treatment, system geometry, photo-sensors, scintillators, and a more robust ...
Planar image quality comparison between a CdZnTe prototype and a standard NaI(Tl) gamma camera
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2003
A CdZnTe prototype was evaluated along with a standard NaI (Tl) gamma camera for planar imaging p... more A CdZnTe prototype was evaluated along with a standard NaI (Tl) gamma camera for planar imaging performance. A 12× 20cm2 CdZnTe gamma camera comprised of 15 Imarad modules and a 3/8-in. thick NaI (Tl) gamma camera were used. A 2D brain slice phantom ...
Uploads
Papers by SAMIR CHOWDHURY