Midjourney Medical

Technical concept & feasibility

• Device is described as “full-body ultrasonic CT” using hundreds of thousands of transducers in water to reconstruct a 3D scan in ~60 seconds.
• Some with imaging backgrounds say USCT is real, used in research and breast imaging; submersion improves coupling (water–skin interface).
• Radiologists and imaging engineers note current sample images look low-detail compared to conventional ultrasound, CT, and MRI and doubt claims of “MRI-level or better” resolution, especially for deep structures, lungs (air), and brain (skull blocks sound).
• Others question data-rate claims (petabytes per scan) as marketing spin; actual pipelines would likely downsample heavily on FPGAs/compute nodes.

Medical value, false positives & overdiagnosis

• Many posters argue mass full‑body scanning of asymptomatic people is likely harmful: high false‑positive rates, “incidentalomas,” cascades of follow‑up tests, biopsies, surgery, anxiety, and system overload.
• Bayes’ theorem is repeatedly invoked: for low-prevalence diseases, even highly accurate tests produce mostly false positives.
• Counter‑view: cheap, frequent longitudinal scans (trends over time vs. one‑off snapshots) plus better models might eventually distinguish benign quirks from dangerous changes and radically advance medical understanding.

Regulation, liability & “spa” positioning

• Strong concern that marketing as a spa/wellness service is an FDA/regulatory workaround; skeptics say it should first prove clinical utility in hospitals and trials, not med‑spas.
• Questions about who reads scans, who is liable for missed findings, and whether non‑diagnostic “body composition maps” will still be interpreted quasi‑medically by users and some doctors.

Scale, economics & target users

• The stated goal (50k scanners, capacity for 1B scans/month) is widely viewed as mathematically and logistically unrealistic given scan time, cleaning, staffing, and infrastructure.
• Many think early adopters will be wealthy biohackers, not “a billion people,” and compare it to executive physicals and other luxury screening services.

Data, privacy & AI

• Some see the main play as building a massive unlabeled imaging dataset to train health models (analogous to LLMs on text).
• Others are uneasy about a generative‑image company owning full‑body 3D medical data, with little mention of privacy, governance, or openness.

Overall sentiment

• Mixed but skewed skeptical: admiration for ambition and hardware, but strong Theranos comparisons, concerns about hype, lack of clinical evidence, and the risk of widespread over‑diagnosis.