Deep Learning Reconstruction for 9-View Dual Energy CT Baggage Scanner
For homeland and transportation security applications, 2D X-ray explosive detection system (EDS) have been widely used, but they have limitations in recognizing 3D shape of the hidden objects. Among various types of 3D computed tomography (CT) systems to address this issue, this paper is interested in a stationary CT using fixed X-ray sources and detectors. However, due to the limited number of projection views, analytic reconstruction algorithms produce severe streaking artifacts. Inspired by recent success of deep learning approach for sparse view CT reconstruction, here we propose a novel image and sinogram domain deep learning architecture for 3D reconstruction from very sparse view measurement. The algorithm has been tested with the real data from a prototype 9-view dual energy stationary CT EDS carry-on baggage scanner developed by GEMSS Medical Systems, Korea, which confirms the superior reconstruction performance over the existing approaches.
Code (0)
등록된 구현이 없습니다.
Tasks
3D ReconstructionComputed Tomography (CT)CT ReconstructionDeep LearningSimilar Papers 제목 키워드 기반
DCNNs: A Transfer Learning comparison of Full Weapon Family threat detection for Dual-Energy X-Ray Baggage Imagery
Recent advancements in Convolutional Neural Networks have yielded super-human levels of performance in image recognition tasks [13, 25]; however, with increasing volumes of parcels crossing UK borders each year, classifi…
ClassificationGeneral ClassificationTransfer LearningA Splitting-Based Iterative Algorithm for GPU-Accelerated Statistical Dual-Energy X-Ray CT Reconstruction
When dealing with material classification in baggage at airports, Dual-Energy Computed Tomography (DECT) allows characterization of any given material with coefficients based on two attenuative effects: Compton scatterin…
CT ReconstructionGeneral ClassificationGPUMaterial ClassificationFan-Beam CT Reconstruction for Unaligned Sparse-View X-ray Baggage Dataset
Computed Tomography (CT) is a technology that reconstructs cross-sectional images using X-ray images taken from multiple directions. In CT, hundreds of X-ray images acquired as the X-ray source and detector rotate around…
Computed Tomography (CT)CT ReconstructionTrainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme Occlusion
Detecting baggage threats is one of the most difficult tasks, even for expert officers. Many researchers have developed computer-aided screening systems to recognize these threats from the baggage X-ray scans. However, a…
Instance SegmentationSemantic SegmentationSTING-BEE: Towards Vision-Language Model for Real-World X-ray Baggage Security Inspection
Advancements in Computer-Aided Screening (CAS) systems are essential for improving the detection of security threats in X-ray baggage scans. However, current datasets are limited in representing real-world, sophisticated…
Instruction FollowingLanguage ModelingLanguage ModellingQuestion Answering+3