Fundamentals of Computerized Tomography: Image Reconstruction from Projections

By G. Herman. Advances in Pattern Recognition, 2009

1,236 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

State-of-the-art review on deep learning in medical imaging. (2019, methodology): “In medical imaging, the scanned images of infected/abnormal regions are usually generated using computed tomography (CT) (25), magnetic resonance imaging (MRI) (26) and ultrasound (US) (27).”
Proximal Splitting Methods in Signal Processing (2009, neutral): “In this scenario, the updating rule reads (cid:0) Convergence is guaranteed by Proposition 4.3.”
Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs). (2011, methodology): “The 3D image is subsequently computed from these projection images by a tomographic reconstruction algorithm [4] [5].”
Rows vs. Columns: Randomized Kaczmarz or Gauss-Seidel for Ridge Regression (2015, methodology): “The Kaczmarz method [11] is also known in the tomography setting as the Algebraic Reconstruction Technique (ART) [6, 15, 1, 9].”
Efficient Accelerated Coordinate Descent Methods and Faster Algorithms for Solving Linear Systems (2013, methodology): “It is an algorithmic design principle that has seen great practical success [4], [5], [3] but has been notoriously difficult to analyze.”