Raju Ningappa Mulawade
A5084674863- Radiation Therapy and Dosimetry
- Nuclear Physics and Applications
- Particle Detector Development and Performance
- Radiation Detection and Scintillator Technologies
- Medical Imaging Techniques and Applications
- Cell Image Analysis Techniques
- Remote Sensing and LiDAR Applications
- Anomaly Detection Techniques and Applications
- Advanced MRI Techniques and Applications
- Dark Matter and Cosmic Phenomena
- Electron and X-Ray Spectroscopy Techniques
- Advanced Neural Network Applications
University of Applied Sciences Worms
2021-2025
Abstract Objective. Monolithic active pixel sensors are used for charged particle tracking in many applications, from medical physics to astrophysics. The Bergen pCT collaboration designed a sampling calorimeter proton computed tomography, based entirely on the ALICE PIxel DEtector (ALPIDE). same telescope can be in-situ range verification therapy. An accurate charge diffusion model is required convert deposited energy Monte Carlo simulations cluster of pixels, and estimate energy, given an...
Abstract In this work, we propose a visual analytics system to analyze deep reinforcement learning (deepRL) models working on the track reconstruction of charged particles in field particle physics. The data these are form point clouds with high-dimensional features. We use one existing post hoc saliency methods explainable artificial intelligence (XAI) and extend its adaptation compute attributions for input corresponding output model. Our proposed helps users explore machine model...
Proton computed tomography (pCT) and radiography (pRad) are proposed modalities for improved treatment plan accuracy in situ validation proton therapy. The pCT system of the Bergen collaboration is able to handle very high particle intensities by means track reconstruction. However, incorrectly reconstructed secondary tracks degrade image quality. We have investigated whether a convolutional neural network (CNN)-based filter improve quality.The CNN was trained simulation reconstruction tens...
Abstract The Bergen proton Computed Tomography (pCT) is a prototype detector under construction. It aims to have the capability track and measure ions’ energy deposition minimize uncertainty in treatment planning. high granularity digital tracking calorimeter, where first two layers will act as obtain positional information of incoming particle. remainder calorimeter. Beam tests been performed with multiple beams. These shown that ALPIDE chip sensor can deposited energy, making it possible...
Objective.Proton therapy is highly sensitive to range uncertainties due the nature of dose deposition charged particles. To ensure treatment quality, verification methods can be used verify that individual spots in a pencil beam scanning fraction match plan. This study introduces novel metric for proton quality control based on spots.Approach.We employ uncertainty-aware deep neural networks predict Bragg peak depth an anthropomorphic phantom secondary particle detection silicon pixel...
Objective. Algorithmic differentiation (AD) can be a useful technique to numerically optimize design and algorithmic parameters by, quantify uncertainties in, computer simulations. However, the effectiveness of AD depends on how "well-linearizable" software is. In this study, we assess promising derivative information typical proton computed tomography (pCT) scan simulation is for aforementioned applications. Approach. This study mainly based numerical experiments, in which repeatedly...