Radiologists
Also called Diagnostic radiologist, Radiology physician, Imaging physician, Attending radiologist, Neuroradiologist
In brief
In May 2025, BLS counted 26,770 US radiologists, with median pay of $420,860 a year. Of the BLS counts since 2021, the highest was 31,960, in May 2023. The earliest figure here is an estimate of 1,200 from 1920, not measured the same way as today's count. The last full technology era for radiologists: Teleradiology and voice recognition, 2001 to 2015.
What the sources say
Official outlook
BLS projects employment to grow 3.4% from 2025 to 2035.
Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend.
Last updated .
Cite this page
Future History. (2026, October 11). Radiologists: jobs and pay since 1920 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/29-1224
Future History. "Radiologists: jobs and pay since 1920." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/29-1224.
@misc{futurehistory_29_1224, author = {{Future History}}, title = {Radiologists: jobs and pay since 1920}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/29-1224}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }
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≈ $410,070 in 2024 prices (derived by us, CPI-adjusted)
November 8, 1895: Wilhelm Conrad Roentgen discovers X-rays in his laboratory at the University of Wurzburg while experimenting with cathode-ray tubes. He photographs his wife Anna Bertha's hand -- she reportedly looked at the image of her own skeleton and said "I have seen my death." Roentgen receives the first Nobel Prize in Physics in 1901 for this discovery. Within weeks of his January 1896 publication, physicians across Europe and America are producing X-ray images of bones; within months, X-ray departments exist in major hospitals.
Clarence Dally, glassblower and assistant to Thomas Edison in Edison's X-ray fluoroscope experiments, dies of radiation cancer at age 39 -- often cited as the first American killed by X-ray radiation. Edison himself had stopped X-ray research after Dally's progressive injuries alarmed him. Dally's death and those of other early X-ray workers drove the first systematic discussions of radiation protection in the radiology community and eventually contributed to the formation of international radiation protection bodies.
The American Board of Radiology is incorporated in Washington, D.C. in January 1934, following discussions between the Radiological Society of North America (RSNA, founded 1915), the American Radium Society (ARS), and the American College of Radiology (ACR, founded 1924). The ABR creates the formal credentialing framework that definitively separates the board-certified diagnostic radiologist from the X-ray technician and from the general physician who happens to interpret X-ray films. Subspecialty certificates follow much later: nuclear radiology, neuroradiology, pediatric radiology, and vascular and interventional radiology subspecialty certificates were introduced in 1994.
October 1972: Jamie Ambrose presents EMI CT scanner images at the RSNA annual meeting in Chicago to a standing ovation from 2,000 physicians. The first clinical CT scan had been performed by Godfrey Hounsfield's team at Atkinson Morley's Hospital in London on October 1, 1971; the RSNA presentation was the specialty's first collective encounter with the technology. US hospitals begin installing CT scanners in 1973-1974. The impact on radiology is immediate: CT replaces pneumoencephalography and many myelographic procedures, creates a new high-value billing category, and transforms the specialty's income trajectory. Hounsfield and Cormack receive the Nobel Prize in Physiology or Medicine in 1979.
The Medicare RBRVS (Resource-Based Relative Value Scale) Fee Schedule takes effect January 1, 1992, replacing the "usual and customary charges" model that had governed Medicare physician reimbursement for decades. For radiology, the transition initially preserved the generous reimbursement rates for advanced imaging procedures that the specialty had enjoyed through the late 1980s. Between 1993 and 2008 -- the "bubble years" in radiology compensation -- CT and MRI volumes almost tripled (from 21M to 62M CT and 9.1M to 26.6M MRI annually) and radiologist income rose proportionally, reaching levels that made radiology one of the top-compensated specialties in medicine. The bubble would eventually deflate after the Deficit Reduction Act of 2005 cut advanced imaging reimbursement rates.
Nighthawk Radiology Services is founded by Paul Berger in 2001, stationing US-licensed radiologists in Sydney, Australia to provide overnight and weekend emergency reads for US hospitals at a time-zone-favorable offset. Nighthawk is the first company to operationalize offshore teleradiology at scale; it grows rapidly because PACS deployment has made remote digital reading technically trivial and a genuine radiologist shortage means US hospitals cannot staff 24/7 coverage internally. By 2005, multiple teleradiology companies are operating and the model has expanded from after-hours coverage to daytime overflow reading. Teleradiology simultaneously raises quality concerns (reads without patient encounter, without clinical context) and workforce-flexibility possibilities that reshape how radiology practices structure staffing.
Stanford radiologist Geoff Hinton gives a widely-cited talk at the 2016 NIH suggesting that "we should stop training radiologists now." The statement generates intense debate inside the specialty and outside it. The actual arc from 2016 to 2026 does not validate the prediction: the FDA AI/ML medical device regulatory framework requires radiologist sign-off on every AI-assisted read; imaging volumes have grown 4-6% per year outpacing AI productivity gains; and a genuine radiologist shortage (not a surplus) was the defining workforce story of 2024-2026. The 2016 prediction proved more influential as a cultural event -- it accelerated AI investment in radiology tools -- than as an accurate employment forecast.
Will AI replace radiologists? What the research says
Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.
Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.
What's changing day to day for radiologists
Three parts of your work where AI is already doing real lifting, and what stays yours.
AI is sitting alongside you herePerform AI-assisted worklist triage and prioritize critical imaging studies, reviewing Aidoc, Viz.ai, or RapidAI algorithm flags in the PACS worklist before beginning standard reads
Perform AI-assisted worklist triage and prioritize critical imaging studies, reviewing Aidoc, Viz.ai, or RapidAI algorithm flags in the PACS worklist before beginning standard reads; confirming or overriding AI alerts for ICH (intracranial hemorrhage), LVO (large vessel occlusion), pulmonary embolism, and aortic dissection; escalating confirmed critical findings to the ordering physician and relevant care team via the platform's mobile notification before completing the full report; and documenting the basis for overriding or confirming AI flags in the radiology report.[2],[3],[4]
Worklist prioritization AI (Aidoc, Viz.ai, RapidAI) now runs 24/7 across every qualifying CT and MRI at more than a thousand hospital deployments, surfacing critical findings (ICH, LVO, PE, aortic dissection) in real time before you open the study. Your irreplaceable role is clinical validation: the AI flags a suspected LVO; you confirm it, synthesize the finding with the patient's clinical history, and make the STAT call to neurovascular surgery, the decision-support tool never makes that call. Develop systematic review habits for AI flag accuracy in your practice setting (false-positive rates vary by algorithm and patient population) so you override intelligently rather than reflexively accepting or dismissing AI outputs.
AI is sitting alongside you hereDictate, edit, and sign radiology reports: using Nuance PowerScribe One with Smart Reporting AI and Rad AI Impressions to draft and auto-populate structured report sections from finding dictation
Dictate, edit, and sign radiology reports: using Nuance PowerScribe One with Smart Reporting AI and Rad AI Impressions to draft and auto-populate structured report sections from finding dictation; reviewing AI-generated impression drafts matched to your language patterns for clinical accuracy; editing for appropriate hedging language, clinical urgency signaling, and actionable follow-up recommendations; and signing the final report as the radiologist of record with full medico-legal accountability for the diagnostic conclusion.[5],[6],[1]
Rad AI Impressions saves radiologists more than an hour per shift by drafting the impression section from your dictated findings, matched to your individual language patterns so the output reads like your own reports. PowerScribe One's Smart Reporting auto-populates structured finding templates. Your clinical role shifts from generating prose to validating it: catching hedging errors (a "possible" that should be "probable"), ensuring the impression integrates all findings rather than just the AI-salient ones, and adding the clinical context and management urgency language that distinguishes a radiologist report from a finding list. Invest in learning the specific failure modes of your reporting AI, impression-generation tools occasionally drop minor findings or misjudge priority ordering, so your editing is targeted rather than comprehensive re-dictation.
AI is sitting alongside you hereInterpret screening mammography studies using AI-assisted second-reader tools, reviewing digital breast tomosynthesis (DBT) datasets with iCAD ProFound AI and Lunit Insight MMG case scores and lesion markings overlaid in the reading workstation
Interpret screening mammography studies using AI-assisted second-reader tools, reviewing digital breast tomosynthesis (DBT) datasets with iCAD ProFound AI and Lunit Insight MMG case scores and lesion markings overlaid in the reading workstation; synthesizing AI finding confidence scores with independent visual assessment for calcification clusters, masses, architectural distortions, and asymmetries; deciding on BI-RADS category and management recommendation (return to screening, short-interval follow-up, diagnostic workup, biopsy) based on the radiologist's integrated judgment; and documenting the basis for overriding or confirming AI markings in the mammography report.[10],[9]
iCAD ProFound AI increased cancer detection rate by 8% and reduced false positives by 37% vs. unassisted reading (Radiology 2024 multi-reader study); Lunit Insight MMG achieves 99% sensitivity deployed at 2,400+ hospitals. These tools function as validated second readers, and the evidence base for their accuracy is now strong enough that reading without AI assistance at a facility that has it may be a standard-of-care question. Your role is the final arbiter: the AI cannot account for subtle asymmetry vs. prior, implant artifact, known biopsy site, or the patient's self-reported breast density concerns. Subspecializing in breast imaging and developing expertise in DBT + AI-assisted interpretation is one of the clearest routes to a higher-CRI, higher-compensation radiology subspecialty as AI drives volume capacity upward.
Where radiologists go next
Natural next steps for someone with your foundation: not exits, evolutions.
- Medical and Health Services Managers
- US median pay
- $123,860 (May 2025)
- BLS outlook 2025-35
- +24.2%
- Health Informatics SpecialistsNo timeline for this role yet
- Cardiologists
- US median pay
- $496,010 (May 2025)
- BLS outlook 2025-35
- +4.8%
What each move takes
Medical and Health Services Managers
Radiologists who develop radiology department leadership experience (quality, AI governance, PACS administration, subspecialty program development) are well positioned for Chief of Radiology, Radiology Department Chair, Chief Medical Officer (CMO), and Chief Medical Informatics Officer (CMIO) roles. As health systems evaluate many FDA-cleared AI imaging tools, need to manage PACS-to-cloud migration decisions, and build AI imaging programs that meet ACR accreditation standards, they urgently need physician executives who understand radiology AI from the inside. The ACR fellowship (FACR) and an MHA or MBA with healthcare focus are the credentialing stepping stones.
- · Radiology department administration: staffing models, productivity benchmarking (RVU-based), scheduling optimization, teleradiology integration and vendor oversight
- · Healthcare AI governance: FDA AI/ML medical device regulatory framework, algorithm validation methodology, clinical AI integration policy, vendor contract negotiation for imaging AI tools
- · PACS and radiology informatics: PACS selection and administration, DICOM and HL7 integration, RIS-PACS-EHR workflow architecture, the technical foundation for CMIO-track roles
- · Healthcare finance: radiology reimbursement (RVU system, global vs. technical vs. professional components, ACR fee schedule), revenue cycle, value-based imaging program development
- · Leadership credentials: ACR Fellowship (FACR), MBA or Master of Health Administration (MHA), ACR Radiology Leadership Institute (RLI) program, formal pathways for radiology leaders
How has the work of radiologists changed since 1896?
The tools that defined the work, one line per era. Select an era to see how it reshaped the work.
Fluoroscopic screen and photographic plate (wet-plate and dry-film X-ray era)
The first radiologists worked with photographic plates coated in silver bromide or later in barium-lead sulfate, requiring wet darkroom processing. Fluoroscopy -- projecting a live X-ray image onto a fluorescent screen -- allowed real-time imaging but required the radiologist to work in a darkened room with eyes dark-adapted for many minutes before each session. Interpretation was qualitative: a practitioner's skill was primarily the ability to recognize normal from abnormal anatomy in a single-modality shadow image. Radiation doses were massive by modern standards -- protective gloves and aprons were not standardized until the 1920s and lead shielding was only gradually adopted after the deaths of the early martyrs demonstrated cumulative dose effects.
Effect on the workThe first generation of radiologists was small -- perhaps more than a thousand practitioners nationally by 1920 -- and self-selected for tolerance of physical risk. Radiation injury substantially shortened the careers and lives of the earliest practitioners, creating persistent demand for trained replacements even as the specialty was professionalizing.
Film-screen radiography + fluoroscopy (film, darkroom, lightbox era)
The dominant radiology workflow from the 1930s through the 1970s: X-ray film exposed in a cassette, developed in a darkroom, and hung on an illuminated lightbox for interpretation. The radiologist's entire cognitive process was conducted over that lightbox, with physical films stored in manila envelopes in hospital filing systems. Contrast agents (barium sulfate for gastrointestinal studies, iodinated contrast for vascular and urinary imaging) expanded the range of conditions that plain X-ray could visualize. Nuclear medicine as a distinct sub-specialty emerged in the 1950s and 1960s with the introduction of technetium-99m (1964) as a practical radiotracer. By the late 1960s a complete radiology department included fluoroscopy suites, a film processing darkroom, nuclear medicine cameras (gamma cameras), and diagnostic ultrasound units -- all interpreted by radiologists from static film or Polaroid snapshots.
CT scanner (EMI/Hounsfield 1971 prototype; first US clinical installations 1973-1974)
Godfrey Hounsfield at EMI Central Research Laboratories performed the first clinical CT scan at Atkinson Morley's Hospital in London on October 1, 1971. At the October 1972 Chicago meeting of the Radiological Society of North America, Jamie Ambrose presented EMI scanner images to 2,000 assembled physicians and received a standing ovation. US hospitals began installing CT scanners in 1973-1974. The impact on radiology was immediate and transformative: CT produced cross-sectional anatomy in three dimensions with tissue-density differentiation that plain X-ray could not approach, replacing invasive pneumoencephalography (air injected into the brain ventricles) and myelography (dye injected into the spinal canal) for many neurological conditions. Hounsfield and Cormack received the 1979 Nobel Prize in Physiology or Medicine. CT created an entirely new category of radiologist expertise and -- more importantly for the specialty's economics -- justified a new, higher-value billing category that drove radiologist income growth throughout the 1980s.
Effect on the workCT expanded the scope and economic value of radiology more than any prior technology. Between 1975 and 1985, the number of CT scanners in the US grew. Radiology department volume and revenues grew proportionally; the specialty that had been modestly compensated relative to procedural specialties became one of the highest-paid in medicine by the late 1980s.
MRI (first commercial scanner 1980; clinical deployment widespread by mid-1980s)
Raymond Damadian's team produced the first human body MRI scan on July 3, 1977 -- a cross-section of an assistant's chest that took five hours to acquire. FONAR Corporation produced the first commercial MRI scanner in 1980; General Electric, Siemens, and Philips entered the market rapidly thereafter. By the mid-1980s, major academic medical centers and large community hospitals were installing MRI units. MRI's impact on radiology was at least as profound as CT: it provided superior soft-tissue contrast (critical for brain, spine, musculoskeletal, and cardiovascular imaging) without ionizing radiation. The specialty now required radiologists with expertise in not one but two fundamentally different physics platforms. MRI created two new economic drivers: a new high-value billing category, and a strong competitive moat around radiologist expertise -- MRI interpretation required deep technical understanding of pulse sequences, artifact recognition, and tissue characterization that general practitioners could not acquire informally.
Effect on the workBetween 1995 and 2006, MRI study volumes in the US nearly tripled per year. The same period saw radiologist compensation reach historic highs, driven by both MRI and CT volume growth under a reimbursement system that valued advanced imaging generously.
PACS and DICOM (filmless digital radiology; DICOM standard published 1993)
The concept of a Picture Archiving and Communication System (PACS) was first articulated in 1982; Dr. Andre Duerinckx coined the term "PACS" in 1981. Early PACS deployments appeared at academic centers from the mid-1980s, but the technology that made interoperability possible was the DICOM standard (Digital Imaging and Communications in Medicine), published in 1993 and establishing a universal format for medical image storage and exchange. PACS transformed the radiologist's work environment from a physical space -- a reading room with hanging lightboxes and film jackets -- into a digital workstation. Studies were read from high-resolution monitors, not from film; prior comparisons were retrieved instantly from archive rather than manually tracked from a film library; radiologists could read from any workstation, including remotely. The productivity effect was dramatic: a radiologist who read many studies per day on film could read more than a hundred studies per day on a digital workstation. This throughput increase drove a substantial income boom in the 1990s and early 2000s and simultaneously created the technical infrastructure that teleradiology (and eventually AI-integrated reading) would later use.
Effect on the workPACS deployment contributed directly to the "bubble years" (1993-2008) in radiology compensation. The same technology also created the infrastructure for offshore teleradiology (Nighthawk Radiology, founded 2001) -- US-licensed radiologists in Australia and Switzerland reading after-hours cases for US hospitals -- which was a direct consequence of the radiologist shortage that PACS-enabled productivity gains had deferred but not eliminated.
Teleradiology and voice recognition (remote reading; Dragon NaturallySpeaking in radiology)
Nighthawk Radiology Services, founded by Paul Berger in 2001, stationed US-licensed radiologists in Australia and later Switzerland to provide nighttime and weekend reading for US hospitals at a favorable time-zone offset. The company grew rapidly by addressing a genuine workforce crisis: there were not enough radiologists to staff 24/7 emergency reads at every US hospital, and PACS had made remote reading technically feasible. By 2005, multiple teleradiology companies were operating and the model had spread beyond after-hours coverage to daytime "overflow" reading for high-volume practices. Simultaneously, voice recognition software (Dragon NaturallySpeaking, later Nuance PowerScribe) replaced tape-recorded dictation routed to transcriptionists, reducing the reporting cycle from hours to minutes. These two changes -- remote reading and instant voice-to-text -- rewired the specialty's workflow and economics and created the infrastructure upon which AI-assisted reporting would later be built.
FDA-cleared AI triage and reporting algorithms (Aidoc 2016, Viz.ai 2018, Rad AI 2020+)
The first wave of FDA-cleared radiology AI tools reached clinical deployment between 2016 and 2021. Aidoc (founded 2016) built a platform of many FDA-cleared algorithms that run continuously on every qualifying CT and MRI in the PACS, flagging critical findings (intracranial hemorrhage, pulmonary embolism, large vessel occlusion, aortic dissection) before the radiologist opens the study. Viz.ai (founded 2018, many FDA-cleared algorithms, 2,500+ hospital deployments) and RapidAI (many FDA-cleared modules, 2,500+ hospitals) addressed stroke and vascular disease triage. Nuance PowerScribe One's AI-powered Smart Reporting and Rad AI Impressions (launched 2020) began automating the routine measurement and impression-writing tasks that had consumed the most time in high-volume reads. By 2025, roughly 40% of US radiology practices had deployed at least one FDA-cleared AI algorithm in routine clinical workflow; radiology accounts for approximately 75% of all FDA AI/ML medical device authorizations. The key structural feature is regulatory: all FDA-cleared radiology AI is classified as decision support -- the radiologist retains diagnostic authority, signs the report, and bears malpractice liability. No FDA-cleared tool operates autonomously without radiologist attestation, and the regulatory pathway for autonomous AI radiologist replacement does not exist.
Effect on the workAI triage reduces time-to-critical-finding notification by 50-80% at deployment sites; AI impression generation recovers more than an hour per radiologist shift; image enhancement AI (Subtle Medical SubtleMR/SubtlePET) enables 50-80% faster scan acquisition. The net effect across deployed sites is radiologist augmentation: more studies interpreted per radiologist-day, not headcount reduction.
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Browse all rolesRadiologists employment and pay by year
View all 11 years of cited US data, each linked to its source
| Year | US employment | Annual pay (median unless marked) | Source | Report |
|---|---|---|---|---|
| 1920 | 1,200 | n/a | Est., American Roentgen Ray Society Researched context | Report |
| 1960 | 8,000 | n/a | Est., American Board of Radiology Researched context | Report |
| 1985 | n/a | $180,000 | Est., Student Doctor Network Researched context | Report |
| 1995 | 27,906 | n/a | Est., Sunshine et al Researched context | Report |
| 2000 | n/a | $310,000 | Est., SalaryDr Researched context | Report |
| 2011 | 38,875 | n/a | Est., Bhargavan-Bhatt et al. (2015) Researched context | Report |
| 2021 | 29,530 | n/a | BLS OEWS May 2021 Official statistic | Report |
| 2022 | 29,250 | n/a | BLS OEWS May 2022 Official statistic | Report |
| 2023 | 31,960 | n/a | BLS OEWS May 2023 Official statistic | Report |
| 2024 | 26,290 | n/a | BLS OEWS May 2024 Official statistic | Report |
| 2025 | 26,770 | $420,860 | BLS OEWS May 2025 Official statistic | Report |