[AINews] Midjourney Medical: scan your organs like you step on a scale

· Source: Latent.Space - Www.latent.space · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, Robotics & Autonomous Systems · Depth: Advanced, extended

Summary

Midjourney has unveiled a medical imaging initiative, introducing the Midjourney Scanner and an associated Midjourney Spa. The Scanner is a prototype full-body ultrasonic CT system, described as the "first new whole-body medical imaging modality in 50 years," utilizing ultrasound instead of radiation. It features 358,000 ultrasonic elements across 40 systems in a 70 cm ring, capturing data at 17 GB/s for 40 GB per body slice, with reconstruction on 21 servers claiming 2 PFLOPS compute. Currently, Gen 1 scans take around 20 minutes, with a goal of several hundred slices in 60 seconds and 0.5 mm resolution. The first Midjourney Spa, a 25,000 sq ft facility with 9-10 scanners, is slated for a late 2027 opening in San Francisco. Midjourney, self-funded and without investors, is discussing regulatory paths with the FDA, initially focusing on body composition. The long-term vision includes a fleet of 50,000 scanners enabling a billion scans monthly, aiming for frequent, cheap, and preventive health tracking.

Key takeaway

For AI Scientists or Directors of AI/ML evaluating future healthcare infrastructure, Midjourney's ultrasonic CT scanner and spa concept signals a significant, self-funded bet on integrated hardware and AI for physical world sensing. You should recognize this as a potential model for generating vast, longitudinal health data, but also critically assess the substantial regulatory, clinical validation, and data privacy challenges inherent in moving from prototype to widespread diagnostic utility.

Key insights

Midjourney is pioneering a full-body ultrasonic CT system for accessible, frequent personal health monitoring.

Principles

Method

A full-body ultrasonic CT system uses 358,000 transducers in a water-immersed ring to capture high-volume data for server-based reconstruction.

In practice

Topics

Best for: AI Scientist, Director of AI/ML, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Latent.Space - Www.latent.space.