In: Medical Imaging

Four overlays of a simulated pelvic X-ray image. The top left has no overlay. The top right has anatomical landmarks labeled. The bottom left shows semantic segmentation annotations for the bones and orthopedic hardware. The bottom right are more specific segmentations for bony corridors that the procedure is targeting.

X-ray vision: Tech could improve efficiency of pelvic fracture surgery

Johns Hopkins researchers harness the power of machine learning to develop a first approach to X-ray-guided surgical phase recognition.

African American male patient during ultrasound thyroid gland examination at the clinic.

Medical imaging fails dark skin. Researchers fixed it.

A Johns Hopkins University-led team found a way to deliver clear pictures of anyone's internal anatomy, no matter their skin tone.

Positioning of the robot end effector and neuroendoscope in relation to a head phantom for robot-assisted 3D neuroendoscopy.

Navigational technology used in self-driving cars aids brain surgery visualization

Johns Hopkins researchers demonstrate the promise of “augmented endoscopy,” a real-time neurosurgical guidance method that uses advanced computer vision techniques.

Headshot of Muyinatu A. Lediju Bell.

Muyinatu Bell awarded $1.5 million NIH grant

John C. Malone Associate Professor of Electrical and Computer Engineering Muyinatu A. Lediju Bell has received a four-year, $1.5 million R01 grant from the National Institutes of Health to develop new technology for photoacoustic-guided hysterectomies in an effort to make the procedures safer via informative, real-time feedback.

An abstract background suggesting red and green fiber optic cables.

Photoacoustic imaging gets flexible

In an effort to improve real-time surgical visualization and reduce potential patient discomfort and injury, Johns Hopkins researchers have verified the accuracy and applicability of a minimally invasive live medical imaging method in a new study.

Headshots of Chien-Ming Huang and Paul Yi.

Malone faculty win DELTA Award

Their winning proposal will receive up to $75,000 to help innovate learning through technology.