In: Medical Imaging

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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.

Muyinatu “Bisi” Bell, center, with PULSE Lab members.

Sharper, safer, more inclusive medical imaging

Backed by NIH funding, Muyinatu “Bisi” Bell’s innovative work is enhancing diagnostic accuracy, improving surgical precision, and ensuring equitable health care for all patients.

Headshot of Muyinatu A. Lediju Bell.

Muyinatu Bell to develop imaging software for ARPA-H-funded lung cancer project

The $13 million award from the Advanced Research Projects Agency for Health will go toward developing a transformative diagnostic tool for lung cancer detection.

Graphic of arrows pointing up. SURPASS BEYOND POSSIBLE.

Malone researchers poised to create transformative technologies

Malone researchers are part of two of the four boundary-pushing proposals funded in this year’s cycle of the SURPASS initiative.