A set of algorithms is presented for direct deconvolution of the residue signal of an organ with the input signal to the organ. The deconvolution process yields the residual impulse response from which the distribution of transit times and the important mean transit time can be readily determined. The deconvolution method is based on the Laplace transform and it requires that the input signal can be fitted with an expression consisting of one, two or three exponentials with or without a bolus term at zero time or a constant term. These types of exponential expressions for the input signal cover a wide range of the input signals encountered in nuclear medicine applications. Simulation studies of the residue signal by convolution of various input signals with a number of residual impulse response models yielded an excellent accuracy of the deconvoluted residual impulse response for a suitably small sampling time. The simulations provide an opportunity to understand further the shapes of the residue curves depending on the shape of the input signal and the distribution of transit times. Simulations with Gaussian-distributed noise and noise spikes superimposed on the residue signal were also made to investigate the robustness of the direct deconvolution algorithm using apparently real-life data.
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Front Robot AI
January 2025
Department of Materials and Production, Aalborg University, Aalborg, Denmark.
Object pose estimation is essential for computer vision applications such as quality inspection, robotic bin picking, and warehouse logistics. However, this task often requires expensive equipment such as 3D cameras or Lidar sensors, as well as significant computational resources. Many state-of-the-art methods for 6D pose estimation depend on deep neural networks, which are computationally demanding and require GPUs for real-time performance.
View Article and Find Full Text PDFCancer is a condition in which cells in the body grow uncontrollably, often forming tumours and potentially spreading to various areas of the body. Cancer is a hazardous medical case in medical history analysis. Every year, many people die of cancer at an early stage.
View Article and Find Full Text PDFAppl Radiat Isot
March 2025
Technical Physics Division, Bhabha Atomic Research Centre, Mumbai, India.
This study shows an implementation of neutron-gamma pulse shape discrimination (PSD) using a two-dimensional convolutional neural network. The inputs to the network are snapshots of the unprocessed, digitized signals from a BC501A detector. By exposing a BC501A detector to a Cf-252 source, neutron and gamma signals were collected to create a training dataset.
View Article and Find Full Text PDFAcc Chem Res
January 2025
Department of Chemistry, Ben-Gurion University of the Negev, Be'er Sheva 84105, Israel.
ConspectusA key challenge in modern chemistry research is to mimic life-like functions using simple molecular networks and the integration of such networks into the first functional artificial cell. Central to this endeavor is the development of signaling elements that can regulate the cell function in time and space by producing entities of code with specific information to induce downstream activity. Such artificial signaling motifs can emerge in nonequilibrium systems, exhibiting complex dynamic behavior like bistability, multistability, oscillations, and chaos.
View Article and Find Full Text PDFElife
January 2025
Cognitive Neuroscience Department, University of Bielefeld (DE), Bielefeld, Germany.
Audiovisual information reaches the brain via both sustained and transient input channels, representing signals' intensity over time or changes thereof, respectively. To date, it is unclear to what extent transient and sustained input channels contribute to the combined percept obtained through multisensory integration. Based on the results of two novel psychophysical experiments, here we demonstrate the importance of the transient (instead of the sustained) channel for the integration of audiovisual signals.
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