Three-D took on a new dimension at the European Congress of Radiology, where Philips Medical systems combined a big-screen LCD with algorithms developed initially to convert DVD-based movies into 3D.
Three-D took on a new dimension at the European Congress of Radiology, where Philips Medical systems combined a big-screen LCD with algorithms developed initially to convert DVD-based movies into 3D.
The combination, oriented toward medical imaging, produced striking images of the brain with vasculature protruding, cutaways of the human skull, an aneurysm bulging between two obviously ineffective stents, and a shot of the abdomen with an interventional tool transecting tissue. All were hanging in air, projecting a realism not possible on conventional flat screens.
Sophie Perceval, Philips marketing manager for cardiovascular x-ray, noted that the technology, a work-in-progress, is being examined for its value as a review medium rather than for diagnostic applications. The images take shape only when viewed from a meter or more away, a distance necessary for the eye to appreciate the illusion of 3D. They might provide physicians another perspective on data, but their true clinical value, if any, remains to be determined.
The concept behind the innovative display, according to a source at Philips, came from the consumer side of the company. The algorithms behind the medical projections were developed initially to reformat Hollywood-style movies played at home.
Philips must now decide whether these algorithms might be leveraged in medical imaging. One thing was certain at the ECR: They can stop radiologists in their tracks.
In the often-bustling aisle by the Philips booth, visitors in a hurry to get where they were going glanced the 3D images hanging in space, instinctively stepped back, and paused.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
April 15th 2024Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
MRI-Based AI Model Shows Promise in Predicting Lymph Node Metastasis with Breast Cancer
April 15th 2024For the prediction of axillary lymph node metastasis in patients with breast cancer, an MRI-based, 4D convolutional neural network model demonstrated an AUC of 87 percent and sensitivity of 89 percent, according to new research.