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Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography

As of 8 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2509.08973.

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2509.08973 v1

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Outbound references

Observation ba409873-d598-4fec-98ec-58f270d9e6ff · outbound

This paper cites an unresolved cited work.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Unresolved cited work

Reference 1

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This paper cites Dental cone beam CT and its justified use in oral health care.J Belg Soc Radiol., 94(5):254–265, 2011.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Dental cone beam CT and its justified use in oral health care.J Belg Soc Radiol., 94(5):254–265, 2011

Reference 2

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This paper cites Introduction of portable computed tomography scanners, in the treatment of acute stroke patients via telemedicine in remote communities.Int J Stroke, 5(2):62–66, 2010.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Introduction of portable computed tomography scanners, in the treatment of acute stroke patients via telemedicine in remote communities.Int J Stroke, 5(2):62–66, 2010

Reference 3

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Observation cc7b427f-0be0-47e5-ad95-5fe1d8280691 · outbound

This paper cites Cone-beam computed tomography with a flat- panel imager: magnitude and effects of x-ray scatter.Med Phys., 28(2):220–231, 2001.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Cone-beam computed tomography with a flat- panel imager: magnitude and effects of x-ray scatter.Med Phys., 28(2):220–231, 2001

Reference 4

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This paper cites The effects of scatter in x-ray computed tomography.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography The effects of scatter in x-ray computed tomography

Reference 5

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Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Unresolved cited work

Reference 6

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Observation 75dc2f6f-53e4-4fcd-98f9-647eb171edef · outbound

This paper cites Scatter rejection by air gaps: An empirical model.Med Phys., 12(3):308–316, 1985.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Scatter rejection by air gaps: An empirical model.Med Phys., 12(3):308–316, 1985

Reference 7

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Observation c44a5139-2738-43c0-a718-e819157d2880 · outbound

This paper cites Efficiency of antiscatter grids for flat-detector CT.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Efficiency of antiscatter grids for flat-detector CT

Reference 8

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Observation 875305ac-1ee0-4b6b-b305-6256ca2b7345 · outbound

This paper cites Scatter correction for cone-beam CT in radiation therapy.Med Phys., 36(6Part1):2258–2268, 2009.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Scatter correction for cone-beam CT in radiation therapy.Med Phys., 36(6Part1):2258–2268, 2009

Reference 9

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This paper cites The effects of compensator and imaging geometry on the distribution of x-ray scatter in CBCT.Med Phys., 38(2):897–914, 2011.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography The effects of compensator and imaging geometry on the distribution of x-ray scatter in CBCT.Med Phys., 38(2):897–914, 2011

Reference 10

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Observation 36c6bb7a-950e-4151-840e-2da0d3ea5c25 · outbound

This paper cites Feasibility of volume-of-interest (VOI) scanning technique in cone beam breast CT—a preliminary study.Med Phys., 35(8):3482–3490, 2008.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Feasibility of volume-of-interest (VOI) scanning technique in cone beam breast CT—a preliminary study.Med Phys., 35(8):3482–3490, 2008

Reference 11

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This paper cites A general framework and review of scatter correction methods in x-ray cone-beam computerized tomography.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography A general framework and review of scatter correction methods in x-ray cone-beam computerized tomography

Reference 12

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This paper cites Accelerating Monte Carlo simulations of photon trans- port in a voxelized geometry using a massively parallel graphics processing unit.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Accelerating Monte Carlo simulations of photon trans- port in a voxelized geometry using a massively parallel graphics processing unit

Reference 13

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This paper cites Monte-Carlo scatter correction for cone-beam computed tomography with limited scan field-of-view.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Monte-Carlo scatter correction for cone-beam computed tomography with limited scan field-of-view

Reference 14

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Observation c1b7d1f8-2442-4f66-943a-1c9b8afaa269 · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 15

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Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Unresolved cited work

Reference 16

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Observation c3227503-6fd5-4d56-954b-d0c7c1aa889c · outbound

This paper cites Projection-domain scatter correction for cone beam computed tomography using a residual convolutional neural network.Med Phys., 46(7):3142–3155, 2019.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Projection-domain scatter correction for cone beam computed tomography using a residual convolutional neural network.Med Phys., 46(7):3142–3155, 2019

Reference 17

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Observation 7c089bb8-b559-495b-aa7f-444d307d8671 · outbound

This paper cites A deep learning approach to estimate x-ray scatter in digital breast tomosynthesis: From phantom models to clinical applications.Med Phys., 50(8):4744–4757, 2023.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography A deep learning approach to estimate x-ray scatter in digital breast tomosynthesis: From phantom models to clinical applications.Med Phys., 50(8):4744–4757, 2023

Reference 18

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Observation f2b73cf7-1f9a-4b61-a618-d390cdc8f5ef · outbound

This paper cites Task-based transferable deep-learning scatter correction in cone beam computed tomography: a simulation study.J.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Task-based transferable deep-learning scatter correction in cone beam computed tomography: a simulation study.J

Reference 19

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This paper cites Deep learning architecture for scatter estimation in cone-beam computed tomography head imaging with varying field- of-measurement settings.J Med Imaging, 11(5):053501–053501, 2024.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Deep learning architecture for scatter estimation in cone-beam computed tomography head imaging with varying field- of-measurement settings.J Med Imaging, 11(5):053501–053501, 2024

Reference 20

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Observation 15e5c9ec-5542-4224-9154-505f77f429d6 · outbound

This paper cites Deep learning-based forward and cross-scatter correction in dual-source CT.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Deep learning-based forward and cross-scatter correction in dual-source CT

Reference 21

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Observation 905e477f-eb2b-4d3e-aeae-fe1021f41a34 · outbound

This paper cites Utilizing U-Net architec- tures with auxiliary information for scatter correction in CBCT across different field-of-view settings.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Utilizing U-Net architec- tures with auxiliary information for scatter correction in CBCT across different field-of-view settings

Reference 22

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Observation 2eb7c41a-78f8-4fed-b36b-ac14a263379b · outbound

This paper cites Effect of the pixel interpolation method for downsampling medical images on deep learning accuracy.J Comput Commun., 9(11):150–156, 2021.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Effect of the pixel interpolation method for downsampling medical images on deep learning accuracy.J Comput Commun., 9(11):150–156, 2021

Reference 23

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This paper cites The impact of downsampling methods 18 on face recognition in electronic identity card.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography The impact of downsampling methods 18 on face recognition in electronic identity card

Reference 24

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Observation 27781eb3-6f7b-418d-b01c-8f12a21e85f9 · outbound

This paper cites A deep learning-based scatter correction of simulated x-ray images.Electronics, 8(9):944, 2019.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography A deep learning-based scatter correction of simulated x-ray images.Electronics, 8(9):944, 2019

Reference 25

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Observation a1e826e3-4a8a-467f-8596-032836259cca · outbound

This paper cites Evaluation of cbct scatter correction using deep convolutional neural networks for head and neck adaptive proton therapy.Phys Med Biol., 65(24):245022, 2020.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Evaluation of cbct scatter correction using deep convolutional neural networks for head and neck adaptive proton therapy.Phys Med Biol., 65(24):245022, 2020

Reference 26

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This paper cites PENELOPE-2006: A code sys- tem for Monte Carlo simulation of electron and photon transport.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography PENELOPE-2006: A code sys- tem for Monte Carlo simulation of electron and photon transport

Reference 27

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Observation 5fbd069e-ed48-43b4-895f-2924075eb74b · outbound

This paper cites Deep Learning Based Projection Domain Metal Segmentation for Metal Artifact Reduction in Cone Beam Computed Tomography.IEEE Access, 11:100371–100382, 2023.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Deep Learning Based Projection Domain Metal Segmentation for Metal Artifact Reduction in Cone Beam Computed Tomography.IEEE Access, 11:100371–100382, 2023

Reference 28

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Observation dd5f0433-4c48-4259-b133-180fbcab2881 · outbound

This paper cites Head-and-neck squa- mous cell carcinoma patients with CT taken during pre-treatment, mid- treatment, and post-treatment (HNSCC-3DCT-RT) [Dataset].

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Head-and-neck squa- mous cell carcinoma patients with CT taken during pre-treatment, mid- treatment, and post-treatment (HNSCC-3DCT-RT) [Dataset]

Reference 29

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Observation fef606c5-f2be-4574-840b-676f780e200e · outbound

This paper cites The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository.J Digit Imaging, 26(6):1045–1057, 2013.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository.J Digit Imaging, 26(6):1045–1057, 2013

Reference 30

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This paper cites Pytorch 2: Faster machine learning through dynamic python bytecode transformation and graph compilation.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Pytorch 2: Faster machine learning through dynamic python bytecode transformation and graph compilation

Reference 31

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Observation d13ec371-31b3-4246-a83c-0ea3893a53d2 · outbound

This paper cites Nearest Neighbor Value Interpolation.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Nearest Neighbor Value Interpolation

Reference 32

Resolution
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Observation 40689a9f-eaf2-4593-b205-5ae52feb7374 · outbound

This paper cites Area-based interpolation for scaling of images from a CCD.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Area-based interpolation for scaling of images from a CCD

Reference 33

Resolution
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source=pdf_text observed=2026-08-04T19:58:00.338311Z digest=sha256:6d08f4f60b715cc97c5c075866eefb39e4b1418103863ba49c7b2772079781dc

Observation 3e78849f-da11-4673-aed2-3c4b47852e3c · outbound

This paper cites Survey: Interpolation methods in medical image processing.IEEE Trans Med Imaging, 18(11):1049–1075, 1999.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Survey: Interpolation methods in medical image processing.IEEE Trans Med Imaging, 18(11):1049–1075, 1999

Reference 34

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Observation 8350059f-2481-4ba3-b933-079771dec920 · outbound

This paper cites Cubic convolution interpolation for digital image processing.IEEE Trans Acoust Speech Signal Process., 29(6):1153–1160, 1981.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Cubic convolution interpolation for digital image processing.IEEE Trans Acoust Speech Signal Process., 29(6):1153–1160, 1981

Reference 35

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Observation da7ae234-f483-4251-86e5-f5d7d9c812f7 · outbound

This paper cites Practical cone-beam algorithm.J Opt Soc Am A 1, 1(6):612–619, 1984.

Ultrafast Deep Learning-Based Scatter Estimation in Cone-Beam Computed Tomography Practical cone-beam algorithm.J Opt Soc Am A 1, 1(6):612–619, 1984

Reference 36

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