In: Medical Imaging

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Extreme close-up of a camera lens capturing a brilliant, prismatic light flare with rainbow-colored rays radiating from the center.

High-speed microscope gives instant look inside living tissue

Developed by Johns Hopkins engineers, the new microscope provides unprecedented, real-time views of living tissue to accelerate patient care and medical research.

Four ultrasounds of breasts after mammographies for diagnosis, isolated on black background.

New tech reduces false positives from breast ultrasounds

An advance by Johns Hopkins researchers could spare patients unnecessary follow-up exams and procedures.

PanTS. Pancreatic Tumor Segmentation.

Hold on to your PanTS—there’s a new pancreatic cancer detection dataset in town

Developed by a Johns Hopkins-led research team, the Pancreatic Tumor Segmentation Dataset may be the key for training AI models to detect pancreatic cancer early enough to make a difference in patients' survival.

Graphic of a paper with an arrow pointing to a red dot in the right side of a set of stylized lungs. Report supervision.

For AI tumor detection, a picture isn’t always worth a thousand words

Johns Hopkins researchers have developed a new method that uses existing radiology reports to train AI models to locate tumors on CT scans more quickly and accurately.

Headshot of Zongwei Zhou.

Zongwei Zhou awarded $2.8 million NIH grant

The National Institutes of Health awarded Zhou and his team a four-year, $2.8 million R01 grant to develop an AI system to enhance the detection and monitoring of metastasis in colorectal cancer using patients’ CT scans.

A person in a white doctor's coat gestures to a tablet in their hand. Behind them is an operating room with a C-arm X-ray imaging machine.

Speak and your X-ray will be imaged

Johns Hopkins researchers present the voice-controlled X-ray imaging system that earned a Best Paper Award at IPCAI 2025.