Dr. Hugh Harvey

Artificial Intelligence
Fake views: Generating image data for machine learning
Like a human locked in a white soundless room struggling to make sense of the outside world, artificial intelligence is impossible to achieve without some sort of input, Dr. Hugh Harvey writes. A functional algorithm must use data, he notes.
October 9, 2018
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Artificial Intelligence
Building ethical AI: Why we must demand it
A dark, dystopian future where artificial intelligence (AI) brutally and coldly runs the world and humans serve merely as a biological tool is a real possibility, writes Dr. Hugh Harvey, but how can we avoid this grim prospect? He addresses the question in his new column.
May 15, 2018
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Artificial Intelligence
Separating the art of medicine from artificial intelligence
Is it feasible to develop an artificial intelligence algorithm that can actually "read" chest x-rays? The task is definitely not an easy one and major challenges must be addressed, writes radiologist Dr. Hugh Harvey in his new column.
February 20, 2018
2018 02 20 19 49 7861 Cyber Informatics Head2 400
Artificial Intelligence
Can artificial intelligence enable a 10-minute MRI scan?
Artificial intelligence (AI) algorithms promise to improve the imaging workflow, leading to significantly faster MR image acquisition times as well as vastly improved image quality in low-dose CT images. Consultant radiologist Dr. Hugh Harvey from London investigates in a new column.
January 16, 2018
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Artificial Intelligence
Is medical imaging data ready for artificial intelligence?
Unless you've been shut in a darkened room, you'll have heard about the incoming tsunami of artificial intelligence (AI) algorithms, writes Dr. Hugh Harvey in a special column. But he fears the imaging AI landscape is like the Wild West, and it badly needs a sheriff in town.
October 30, 2017
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MRI safety and radiation-induced cancer risks dominate in 2025
MRI safety topics, along with the risk of cancer caused by overuse of CT, remain central themes for the European medical imaging community, according to our list of top 10 articles.
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Organized Radiology Issues
Who's bidding for glory at the ESR's 2026 election?
Dysplastic glenoid tubercle predisposing patient to recurrent dislocations.
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Is imaging always needed for recurring shoulder dislocations?
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Medical, Legal, and Practice
Take charge of work patterns and look after each other
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12 key points to remember for AI deployment
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MRI safety and radiation-induced cancer risks dominate in 2025
By Philip Ward
MRI safety topics, along with the risk of cancer caused by overuse of CT, remain central themes for the European medical imaging community, according to our list of top 10 articles.
December 18, 2025
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Who's bidding for glory at the ESR's 2026 election?
By Maryam Payne
The European Society of Radiology (ESR) has revealed the candidates for next year's election for Executive Council positions. Voting will last from 8 to 21 January.
December 17, 2025
Eu Ballot Box 400
Is imaging always needed for recurring shoulder dislocations?
By Maryam Payne
A comprehensive audit has shed light on the optimum use of imaging in patients with recurrent dislocations.
December 17, 2025
Dysplastic glenoid tubercle predisposing patient to recurrent dislocations.
Take charge of work patterns and look after each other
By Dr. Paul McCoubrie
In the absence of a magical fairy godmother, we need to take charge of our own work patterns and look after each other, writes Dr. Paul McCoubrie.
December 16, 2025
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12 key points to remember for AI deployment
By Liz Carey
The AI Working Group of the ESR has released a consensus paper about the chain of responsibility for AI as a medical device regulatory compliance issue.
December 15, 2025
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Patients support AI in radiology, but not as standalone reader
By Will Morton
Most patients support the use of AI in radiology, but they’re not ready for it to act as a standalone reader, an Irish survey has found.
December 15, 2025
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Marathon training seems to have no negative impact on heart
By Amerigo Allegretto
Imaging has confirmed that endurance training by marathon runners does not appear to have long-term negative effects on the heart.
December 15, 2025
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MRI casts light on patient outcome after heart attack
By Maryam Payne
Increased volume of fat tissue around the heart tends can be associated with greater myocardial damage after a heart attack, German researchers have reported.
December 12, 2025
Cardiac MRI analysis can provide useful information on epicardial adipose tissue, infarct size, microvascular obstruction, and myocardial edema.
3D-printed prostheses bring hope in conflict zones
By Philip Ward
3D-printing allows for faster, lighter, more affordable, and highly customized prosthetic production, and the technology can help patients regain mobility.
December 11, 2025
A smartphone is used to take an image for a 3D-printed prosthesis.
MRI proves effective for tracking results of obesity interventions
By Kate Madden Yee
MRI is a powerful tool to monitor skeletal muscle adaptations during lifestyle interventions for obesity, researchers noted.
December 10, 2025
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Lung cancer screening: How Croatia does it
By Maryam Payne
The Croatian lung cancer screening program, integrated into the national system and designed for equitable access, could serve as a model for other countries.
December 10, 2025
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AI comes under scrutiny in Swedish prostate MRI study
By Philip Ward
An AI system trained in a screening population has lower specificity than radiologists using PI-RADS v2, but considerable care is vital, researchers from Gothenburg reported in European Radiology on 8 December.
December 9, 2025
Example case from test set with biparametric MRI data, reference segmentation, and output from AI system. The primary MRI assessment resulted in a PI-RADS 5 lesion in the left dorsal part of the peripheral zone and a PI-RADS 4 lesion in the right dorsal part of the peripheral zone (PSA of 11.6 μg/L). Targeted biopsies from both areas showed ISUP-grade 3. All images are from the same slice location, showing a part of both lesions. A T2-weighted (T2W) image. B Diffusion-weighted image with a b-value of 1,500 s/mm2. (C) Apparent diffusion coefficient map. (D) Reference segmentation with white areas representing tumor. (E) Softmax output from AI system. Inset in the lower left corner shows the detection map (cropped around the prostate) with red voxels representing softmax values of 0.99 and yellow voxels representing softmax values of 0.59. (F) T2W image with reference (D) and detection map (inset in E) overlayed, green represents areas in which both the reference and the AI output are positive (true positive voxels for AI), red only positive in reference (false-negative voxels for AI) and blue only segmented by AI (false-positive voxels for AI).
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