Skip to main content

Scientists Discover Way to Send Information into Black Holes Without Using Energy

3 comments

Scientists Create AI-Powered Pen Device That Could Detect Cancer in Real Time

A team of researchers from Rice University and The University of Texas MD Anderson Cancer Center has developed a groundbreaking handheld imaging device that could dramatically improve how cancer is detected. The new technology, called PrecisionView, combines artificial intelligence with advanced optical imaging to help doctors identify cancer in real time without relying heavily on invasive biopsies.

The research was recently published in the journal Proceedings of the National Academy of Sciences and is being seen as a major step forward in medical imaging and early cancer diagnosis.

A New Approach to Detecting Cancer

Early detection remains one of the most important factors in improving cancer survival rates. When cancer is discovered at an early stage, treatment is usually more effective, less invasive, and less expensive. However, many cancers are still diagnosed too late because current diagnostic methods have important limitations.

Today, doctors often rely on biopsies, where a small piece of tissue is removed and sent to a laboratory for analysis. While biopsies are highly useful, they are invasive, time-consuming, and can sometimes miss dangerous areas because only a tiny portion of tissue is sampled.

PrecisionView was designed to solve these problems.

The device is a small handheld endomicroscope, roughly the size of a pen, that allows clinicians to examine tissue directly inside the body with extremely high detail. Instead of removing tissue immediately, doctors can scan large areas in real time and identify suspicious regions instantly.

This could make cancer screening faster, more accurate, and far less invasive for patients.

How PrecisionView Works

What makes PrecisionView unique is the way it combines artificial intelligence with optical engineering.

Traditional medical imaging systems often force doctors to choose between two important features:

  • High image detail

  • Large imaging coverage

Most devices cannot do both at the same time. If they provide detailed cellular images, they usually only capture a very small area. If they scan a larger area, image quality often drops.

PrecisionView breaks this trade-off.

The device uses a specially designed optical component called a phase mask together with a deep learning reconstruction algorithm. Rather than using AI only after the image is captured, researchers used AI to redesign the microscope’s optics themselves.

This approach allows the system to produce high-resolution images over a much larger area while also keeping objects in focus across uneven tissue surfaces.

According to the researchers, PrecisionView achieves:

  • A field of view nearly five times larger than conventional systems

  • A depth of field about eight times greater

  • Cellular-level imaging resolution

  • Real-time imaging at up to 15 frames per second

This means clinicians can move the handheld device naturally while still obtaining sharp images without constant refocusing.

Seeing Cancer More Clearly

One of the most important capabilities of PrecisionView is its ability to visualize two major hallmarks of cancer at the same time.

The system can capture:

  1. Changes in cells within epithelial tissue

  2. Abnormal blood vessel patterns beneath the tissue surface

Epithelial cancers include cancers of the cervix, mouth, skin, and many internal organs. These cancers account for a large percentage of cancer cases worldwide.

Cancerous and precancerous tissues often show abnormal cell nuclei and unusual blood vessel growth. Traditionally, observing both features clearly in one continuous image has been difficult.

PrecisionView changes that.

The device creates detailed maps across several square centimeters of tissue while simultaneously showing cellular structures and vascular patterns. This provides doctors with a more complete picture of what is happening inside the tissue.

Researchers say this could significantly improve a clinician’s ability to distinguish healthy tissue from potentially dangerous lesions.

Why Current Imaging Systems Struggle

Conventional in vivo microscopy systems already offer noninvasive imaging, but they come with several limitations.

Most existing systems have:

  • Small viewing areas

  • Shallow focus depth

  • Difficulty imaging uneven surfaces

  • Limited ability to scan large lesions

These limitations make it difficult to evaluate complex tissue structures or identify the best area for a biopsy.

For example, if a suspicious lesion spreads over a wide area, a doctor may only biopsy one small section. If the sampled region does not contain the most abnormal cells, important warning signs could be missed.

PrecisionView addresses this issue by allowing clinicians to examine much larger tissue regions instantly and in real time.

This could reduce both missed diagnoses and unnecessary biopsies.

Promising Results in Early Studies

The researchers tested PrecisionView in several experiments involving healthy volunteers and human tissue samples containing precancerous changes.

In one study, the device scanned the oral cavities of volunteers and successfully created detailed, high-resolution tissue maps over areas larger than one square centimeter.

In another study involving cervical tissue samples, PrecisionView clearly identified abnormal precancerous regions and distinguished them from surrounding healthy tissue.

These results suggest that the device may become highly useful for detecting cancers of the mouth, cervix, and other epithelial tissues during routine examinations.

Although larger clinical trials are still needed, the early findings are encouraging.

A Low-Cost Solution With Global Impact

Another major advantage of PrecisionView is affordability.

Advanced medical imaging systems are often expensive and difficult to deploy in low-resource regions. Many hospitals and clinics around the world lack access to advanced pathology services, causing delays in diagnosis and treatment.

PrecisionView was intentionally designed to be compact, portable, and relatively inexpensive.

Researchers estimate the device costs around $3,000 to build, far cheaper than many traditional medical imaging systems.

Because it uses simpler components and portable hardware, the device could potentially be used in:

  • Rural clinics

  • Mobile health units

  • Community screening programs

  • Low-resource hospitals

  • Underserved regions with limited pathology infrastructure

This could be especially important in developing countries, where delayed cancer diagnosis remains a major health challenge.

By bringing advanced imaging directly to the point of care, doctors may be able to make faster decisions and begin treatment earlier.

The Role of Artificial Intelligence in Future Medicine

PrecisionView also represents a broader shift in how artificial intelligence is being used in healthcare.

In many medical technologies today, AI is added after data is collected to improve image quality or help analyze results. PrecisionView takes a different approach by integrating AI directly into the design of the imaging hardware itself.

Researchers believe this “co-design” strategy — where hardware and algorithms are developed together — could unlock entirely new medical capabilities.

Instead of simply improving existing systems, AI can help engineers rethink how devices are built from the ground up.

This may lead to future medical tools that are:

  • Smaller

  • Faster

  • More accurate

  • Less expensive

  • Easier to use in everyday clinical settings

What Happens Next?

While PrecisionView has shown strong early performance, researchers emphasize that larger clinical studies are still necessary before the technology becomes widely available.

Future studies will focus on validating diagnostic accuracy across different cancer types and clinical environments.

If successful, the technology could eventually help guide biopsies, support surgical decisions, and improve routine cancer screening procedures worldwide.

The researchers believe the device represents an important glimpse into the future of medical imaging — one where AI and optical engineering work together to make healthcare more accessible, accurate, and effective.

As cancer rates continue to rise globally, technologies like PrecisionView may play a vital role in helping doctors detect disease earlier and save more lives.

Reference: 

  • H. Hou,
  • J. Wu,
  • J. Liu,
  • V. Boominathan,
  • A. Shende,
  • K. Goli,
  • J. Carns,
  • R.A. Schwarz,
  • A.M. Gillenwater,
  • P. Ramalingam,
  • M.P. Salcedo,
  • K.M. Schmeler,
  • T.S. Tkaczyk,
  • J.T. Robinson,
  • A. Veeraraghavan,
  • & R.R. Richards-Kortum,
    •  
  •  
Deep-learning endomicroscope with large field-of-view and depth-of-field for real-time in vivo imaging of epithelial cancer hallmarks, Proc. Natl. Acad. Sci. U.S.A. 123 (20) e2602705123, https://doi.org/10.1073/pnas.2602705123 (2026).

Comments

Post a Comment

Popular

Scientists Discover Way to Send Information into Black Holes Without Using Energy

For years, scientists believed that adding even one qubit (a unit of quantum information) to a black hole needed energy. This was based on the idea that a black hole’s entropy must increase with more information, which means it must gain energy. But a new study by Jonah Kudler-Flam and Geoff Penington changes that thinking. They found that quantum information can be teleported into a black hole without adding energy or increasing entropy . This works through a process called black hole decoherence , where “soft” radiation — very low-energy signals — carry information into the black hole. In their method, the qubit enters the black hole while a new pair of entangled particles (like Hawking radiation) is created. This keeps the total information balanced, so there's no violation of the laws of physics. The energy cost only shows up when information is erased from the outside — these are called zerobits . According to Landauer’s principle, erasing information always needs energy. But ...
3 comments
Read more

Black Holes That Never Dies

Black holes are powerful objects in space with gravity so strong that nothing can escape them. In the 1970s, Stephen Hawking showed that black holes can slowly lose energy by giving off tiny particles. This process is called Hawking radiation . Over time, the black hole gets smaller and hotter, and in the end, it disappears completely. But new research by Menezes and his team shows something different. Using a theory called Loop Quantum Gravity (LQG) , they studied black holes with quantum corrections. In their model, the black hole does not vanish completely. Instead, it stops shrinking when it reaches a very small size. This leftover is called a black hole remnant . They also studied something called grey-body factors , which affect how much energy escapes from a black hole. Their findings show that the black hole cools down and stops losing mass once it reaches a minimum mass . This new model removes the idea of a “singularity” at the center of the black hole and gives us a better ...
Post a Comment
Read more

How Planetary Movements Might Explain Sunspot Cycles and Solar Phenomena

Sunspots, dark patches on the Sun's surface, follow a cycle of increasing and decreasing activity every 11 years. For years, scientists have relied on the dynamo model to explain this cycle. According to this model, the Sun's magnetic field is generated by the movement of plasma and the Sun's rotation. However, this model does not fully explain why the sunspot cycle is sometimes unpredictable. Lauri Jetsu, a researcher, has proposed a new approach. Jetsu’s analysis, using a method called the Discrete Chi-square Method (DCM), suggests that planetary movements, especially those of Earth, Jupiter, and Mercury, play a key role in driving the sunspot cycle. His theory focuses on Flux Transfer Events (FTEs), where the magnetic fields of these planets interact with the Sun’s magnetic field. These interactions could create the sunspots and explain other solar phenomena like the Sun’s magnetic polarity reversing every 11 years. The Sun, our closest star, has been a subject of scient...
Post a Comment
Read more