Thursday, 02 February 2023

DeepTek introduces new AI powered lumbar spine quantification automation tool

04 January 2023 | News

Launches DeepSpine at RSNA 2022 in the US

Pune-based health tech startup DeepTek has announced the global launch of DeepSpine - an artificial intelligence (AI) powered lumbar spine quantification and metrics tool designed to analyse MRI lumbar spine images. The tool was launched at the Radiological Society of North America (RSNA) annual meeting in Chicago, USA.

DeepTek’s new innovation DeepSpine provides AI powered quantification and analysis tool for lumbar spine MRI studies and can assist radiologists, technologists, orthopaedic surgeons and physio experts to get objective automated quantification and other document of lumbar spine, adding value to the radiology reports and decongesting the radiology workflow.

Lower back pain (LBP) affects up to 80%–85% of the population during their lifetime. It is a leading cause of morbidity and disability, with an increasing prevalence due to the steadily aging population worldwide. According to the American College of Radiologists, lumbar spine MRI is the preferred imaging modality to rule out causes of complicated lower back pain and to decide whether conservative or invasive therapeutic approaches should be considered. Subsequently, the number of MRI studies of the lumbar spine has been rising over the last decades at a much higher rate than the number of trained radiologists who could adequately interpret the MR images.

DeepTek has been instrumental in transforming the radiology workflow by leveraging the power of AI. Its AI-powered radiology orchestration solution Augmento has already created waves across the Asia Pacific (APAC) and is also getting deployed in a progressive Singapore health system. Another flagship product by DeepTek is Genki - the AI-powered public health screening solution which is helping medical professionals across India, Philippines, Mongolia, and several other countries in the APAC region to eradicate tuberculosis (TB) by identifying suspected cases promptly and precisely, leading to earlier treatment and better patient care.

 

 

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