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Upgraded Diagnostic Ultrasound Features New Deep Learning Algorithm

By MedImaging International staff writers
Posted on 28 Apr 2016
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Image: The RS80A with Prestige ultrasound system (Photo courtesy of Samsung Medison).
Image: The RS80A with Prestige ultrasound system (Photo courtesy of Samsung Medison).
A global medical equipment company has announced an upgrade for a premium ultrasound imaging system that includes deep learning technology for image analysis of breast lesions.

The goal of the upgraded breast lesion analysis tool is to increase the efficiency of radiologists by providing deep learning algorithm and other imaging enhancements including CEUS (Contrast-enhanced ultrasound) and fusion diagnostic imaging functions.

The Samsung Medison (Seoul, Korea) S-Detect for Breast upgrade for the premium RS80A with Prestige ultrasound system uses big data from many breast exams to provide the characteristics of displayed lesions and an analysis of whether a lesion is malignant or benign. The deep learning algorithm can improve the accuracy of diagnostic image analysis results by providing lesion characteristic analysis, segmentation, and assessment.

The RS80A with Prestige upgrade also includes an improved S-Fusion tool, CEUS+ with VesselMax and FlowMax tools for vessel and blood flow visualization, S-3D arterial analysis for 3-D vessel imaging and simplified artery plaque volume. The upgrade also includes improved near-to-far-field image conformity and reduced signal noise using advanced S-Harmonic technology. The HQ Vision tool enables improved visualization of anatomical structures, increases the reliability of diagnosis for musculoskeletal, and other imaging types.

The new RS80A with Prestige upgrade is currently available in Europe, and the Middle East, and will be launched in China, Russia, and the Americas at a later date.

Professor Han Boo Kyung, radiologist, Samsung Medical Center, said, "We saw a high level of conformity from analyzing and detecting lesion in various cases by using the S-Detect. Users can reduce taking unnecessary biopsies and doctors-in-training will likely have more reliable support in accurately detecting malignant and suspicious lesions."

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