OOIR: Observatory of International Research

Papers

(The H4-Index of Medical Physics is 43. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)

Article	Citations
Machine and deep learning methods for radiomics	224
Report of AAPM Task Group 235 Radiochromic Film Dosimetry: An Update to TG‐55	159
Computer‐aided diagnosis in the era of deep learning	151
Machine learning techniques for biomedical image segmentation: An overview of technical aspects and introduction to state‐of‐art applications	145
Toward data‐efficient learning: A benchmark for COVID‐19 CT lung and infection segmentation	136
Abnormal lung quantification in chest CT images of COVID‐19 patients with deep learning and its application to severity prediction	134
Principles and applications of multienergy CT: Report of AAPM Task Group 291	111
Noise and spatial resolution properties of a commercially available deep learning‐based CT reconstruction algorithm	105
Deep learning based synthetic‐CT generation in radiotherapy and PET: A review	93
Report on G4‐Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group	89
Low‐dose CT image and projection dataset	86
Automated glioma grading on conventional MRI images using deep convolutional neural networks	83
Does FLASH deplete oxygen? Experimental evaluation for photons, protons, and carbon ions	81
Auto‐segmentation of organs at risk for head and neck radiotherapy planning: From atlas‐based to deep learning methods	81
A framework for defining FLASH dose rate for pencil beam scanning	77
Radiobiology of the FLASH effect	70
A new deep convolutional neural network design with efficient learning capability: Application to CT image synthesis from MRI	68
Task group 284 report: magnetic resonance imaging simulation in radiotherapy: considerations for clinical implementation, optimization, and quality assurance	67
Introduction to machine and deep learning for medical physicists	66
Breast tumor segmentation in 3D automatic breast ultrasound using Mask scoring R‐CNN	66
Strategies for effective physics plan and chart review in radiation therapy: Report of AAPM Task Group 275	66
Ultra‐high dose rate electron beams and the FLASH effect: From preclinical evidence to a new radiotherapy paradigm	65
AAPM task group report 302: Surface‐guided radiotherapy	65
Feasibility of proton FLASH irradiation using a synchrocyclotron for preclinical studies	64
Artificial intelligence‐based clinical decision support in modern medical physics: Selection, acceptance, commissioning, and quality assurance	63

Improving CBCT quality to CT level using deep learning with generative adversarial network	62
AAPM Task Group 198 Report: An implementation guide for TG 142 quality assurance of medical accelerators	54
A review of explainable and interpretable AI with applications in COVID‐19 imaging	53
Fully automated multiorgan segmentation in abdominal magnetic resonance imaging with deep neural networks	52
Ultra‐high dose rate dosimetry: Challenges and opportunities for FLASH radiation therapy	52
Treatment response prediction using MRI‐based pre‐, post‐, and delta‐radiomic features and machine learning algorithms in colorectal cancer	51
Machine QA for the Elekta Unity system: A Report from the Elekta MR‐linac consortium	50
Commissioning of an ultra‐high dose rate pulsed electron beam medical LINAC for FLASH RT preclinical animal experiments and future clinical human protocols	50
Report of AAPM Task Group 155: Megavoltage photon beam dosimetry in small fields and non‐equilibrium conditions	50
Report of AAPM Task Group 219 on independent calculation‐based dose/MU verification for IMRT	49
Simultaneous dose and dose rate optimization (SDDRO) for FLASH proton therapy	48
A method of rapid quantification of patient‐specific organ doses for CT using deep‐learning‐based multi‐organ segmentation and GPU‐accelerated Monte Carlo dose computing	48
Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images	48
Repeatability of radiomic features in magnetic resonance imaging of glioblastoma: Test–retest and image registration analyses	47
AAPM Task Group 264: The safe clinical implementation of MLC tracking in radiotherapy	47
Vision Transformer‐based recognition of diabetic retinopathy grade	46
Comparison of CBCT‐based dose calculation methods in head and neck cancer radiotherapy: from Hounsfield unit to density calibration curve to deep learning	44
Technical Note: Dose prediction for head and neck radiotherapy using a three‐dimensional dense dilated U‐net architecture	44
Technical Note: SpekPy v2.0—a software toolkit for modeling x‐ray tube spectra	43
Deep model with Siamese network for viable and necrotic tumor regions assessment in osteosarcoma	43