5 papers
High-Fidelity ROI CT Reconstruction with Limited Quantum Resources via Hybrid Classical-Quantum Refinement
Hyunju Lee, Jeonghwa Lee, Kyungtaek Jun
Quantum optimization for computed tomography (CT) reconstruction is constrained by the number of binary variables required for image representation, making direct whole-image quant…
Quantum-Assisted Tomographic Image Refinement with Limited Qubits for High-Resolution Imaging
Hyunju Lee, Kyungtaek Jun
We propose a quantum-assisted reconstruction framework for high-resolution tomographic imaging that significantly reduces both qubit requirements and radiation exposure. Convention…
Quantum Supremacy in Tomographic Imaging: Advances in Quantum Tomography Algorithms
Hyunju Lee, Kyungtaek Jun
Quantum computing has emerged as a transformative paradigm, capable of tackling complex computational problems that are infeasible for classical methods within a practical timefram…
QUBO Refinement: Achieving Superior Precision through Iterative Quantum Formulation with Limited Qubits
Hyunju Lee, Kyungtaek Jun
In the era of quantum computing, the emergence of quantum computers and subsequent advancements have led to the development of various quantum algorithms capable of solving linear…
Quantum optimization algorithms for CT image segmentation from X-ray data
Kyungtaek Jun
Computed tomography (CT) is an important imaging technique used in medical analysis of the internal structure of the human body. Previously, image segmentation methods were require…