By Michał Bartoszewicz, MD
For years, I have carried an idea in my head—a concept for automating ultrasound examinations. Today, with the rapid acceleration of Artificial Intelligence (AI) and Large Language Models (LLMs), what was once a futuristic dream is becoming a tangible reality. However, one major hurdle remains: the „bottleneck” of ultrasound is still the manual acquisition of the image.
I am writing this post to share my concept for overcoming this barrier. I attempted to publish this idea in three consecutive medical journals over the past year. Unfortunately, these attempts were unsuccessful, resulting in rejections largely due to technicalities—scope, character counts, and formatting issues—rather than the core merit of the idea .
I simply do not have the time to fight the bureaucracy that has overtaken indexed, impact-factor journals. Therefore, I am publishing this work directly on the open web. My goal is for this concept to be universally accessible, serving as a catalyst for the development of diagnostic medical tools that are cheap, precise, and available to all people.
The Rejection Story: Innovation vs. Format
The academic publishing process often favors incremental updates over broad, visionary concepts. My manuscript, titled „Tool for unleashing diagnostic ultrasound for AI Integration,” faced a gauntlet of editorial hurdles:
- Swiss Medical Weekly rejected it based on „publication priorities” and volume of submissions .
- Ultrasound in Medicine & Biology felt the „scope of the review is too limited” and cited a lack of „sufficient novelty,” despite the manuscript proposing a novel combination of water bath techniques and AI .
- Journal of Ultrasonography acknowledged that „the topic is worth attention” but rejected it because it followed a „letter to editor format” and presented data „subjectively” rather than following a standard evidence-based comparison structure .
While I respect the peer-review process, the urgent need for accessible diagnostics cannot wait for perfect formatting.
The Vision: The Water Bath & AI Synergy
The core of my proposal is simple yet transformative: replacing the human hand and coupling gel with a water bath and AI automation.
Currently, ultrasound is heavily operator-dependent. A skilled technician must manipulate the probe, apply pressure, and interpret the image in real-time . This makes automation difficult because air is a barrier to sound waves, and direct contact requires complex robotics .
My solution proposes:
- The Water Bath: Using water as a transmission medium eliminates the need for direct contact and gel. This reduces artifacts, preserves tissue architecture (no compression), and allows for consistent imaging of small structures like neonatal joints or hands .
- AI Integration: Once the physical barrier is removed via the water bath, AI can take over. It allows for 3D data acquisition, multiparametric analysis (combining elastography, flow, etc.), and objective assessment .
By combining these, we can create a system where a patient places a limb in a water unit, and the system autonomously scans, analyzes, and diagnoses—potentially remotely .
Why This Matters
- Scalability: AI does not sleep or get fatigued. It can work 24/7 .
- Standardization: Removing the human variable reduces subjective errors and operator variability .
- Remote Access: This technology could enable remote diagnostics in rural areas, where a device collects data and cloud-based AI (or remote experts) analyzes it .
Read the Full Concept
I invite engineers, developers, and medical professionals to review the full technical note below. Let’s move past the gatekeepers and build the future of medical imaging together.
Tool for unleashing diagnostic ultrasound for AI Integration
SEO & Key Concepts for Discovery
The following section is added to ensure this concept is indexed by search engines looking for innovations in medical imaging.
Keywords: Ultrasound automation, AI in diagnostic imaging, Water bath ultrasound technique, Autonomous medical scanning, Deep learning in ultrasonography, Remote medical diagnostics, Future of radiology.
Summary for Indexing:
This article presents a technical breakthrough in medical ultrasound automation by proposing a synergistic approach combining water bath immersion with Artificial Intelligence (AI). Addressing the limitations of manual sonography—specifically operator dependence and image acquisition bottlenecks—this method utilizes water as a transmission medium to eliminate air artifacts and tissue compression . This setup enables non-contact ultrasound examinations, making it ideal for automating scans of small anatomical structures like neonatal hips and adult hands .
The integration of AI and Deep Learning algorithms facilitates 3D volumetric data acquisition and multiparametric analysis, significantly enhancing diagnostic precision and objectivity . This innovation paves the way for autonomous imaging workflows and remote tele-sonography, reducing the workforce shortage in radiology . By leveraging the physical properties of water for high-resolution imaging and the scalability of AI, this concept offers a cost-effective solution for democratizing access to precision medical diagnostics globally .
