Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups working on solutions for the healthcare sector. As there is a large number of startups working on a wide variety of solutions, we decided to share our insights with you. This time, we are taking a look at 5 promising computer vision startups.
Heat Map: 5 Top Computer Vision Startups
For our 5 top picks, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 5 interesting examples out of 270 relevant solutions. Depending on your specific needs, your top picks might look entirely different.
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ADAS 3D – Medical Imaging
Computer vision and deep learning technologies are used to read and convert 2D scan images into interactive 3D models to enable medical professionals to gain a detailed understanding of a patient’s health condition. This technology helps radiologists inspect scans in-depth and identify disorders easily without spending much time on scanning.
The Spanish startup ADAS 3D, an imaging platform, helps healthcare professionals visualize fibrosis, wall thickness and surrounding anatomical structures of the heart. This software-based image processing tool is used for post-processing cardiovascular enhanced Magnetic Resonance Imaging (MRI) and Computed Tomography Angiography (CTA). This is designed to enable calculation, quantification, and visualization of 3D cardiac imaging data by displaying and quantifying the levels of enhancement.
Oxipit – Automated Report Generation
Computer vision, combined with natural language processing and generation (NLP and NLG) is used to generate reports from computer tomography (CT), X-Rays, and MRIs. The system independently creates reports based on the contents of the images. This saves a lot of time for medical specialists so they don’t have to analyze the images and note down their findings manually.
Oxipit, a Lithuanian computer vision software startup specialized in medical imaging, offers computer-assisted reports for healthcare professionals. Aided with computer vision, various medical procedures like diagnosis, pathology localization, lesion segmentation, volumetric evaluation, gets generated automatically. More than 50 common radiological findings are included for medical professionals to improve analyzing lead time.
Iterative Scopes – Improved Accuracy Of Diagnosis
The use of computer vision in healthcare diagnosis provides high levels of precision by minimizing errors. As computer vision algorithms are trained using a vast amount of training data, it allows detection of even the minimal presence of a condition that may be missed by doctors because of their human limitations, for example, in identifying cancerous cells and tumors from images and biopsy results.
Iterative Scopes, a US software company, provides artificial intelligence (AI) instruments for the gastroenterology practice. Enabled with computer vision and machine learning technology, doctors provide critical healthcare with real-time computer detection, diagnostic, and lesions classification tools. This helps medical professionals improve their accuracy of diagnosis with ease.
Pixee Medical – Technology Enabled Surgical Assistance
Scientists incorporate computer vision and machine learning models to improve surgical precision and accuracy of decisions during complex surgical procedures. Computer vision systems are used to process, correct, and analyze the images of the operating room, the patient’s body, and the surgical tools. This helps to calibrate, orient, and guide surgical movements during the operation enabling medical professionals to improve surgical precision.
Pixee Medical, a French startup, develops computer-assisted surgical tools using augmented reality (AR) and mixed reality (MR). AR tracking tools enabled with computer vision and deep learning help create 3D reconstructed models of bone structure and its anatomical landmarks. Equipped with virtual reality, surgeons plan better for the positioning of the prosthesis and during surgery, align with the patient’s bone with improved precision.
DeepOncology – Timely Detection Of Illnesses
Most fatal illnesses like cancer are treated with a higher chance of success if diagnosed early. Computer vision enables the detection of early symptoms with high certainty owing to its fine-tuned pattern recognition capability. This helps medical professionals to provide prompt and timely treatment to patients and save lives.
DeepOncology AI, an Israeli startup, works with AI in the fields of oncology and radiology. The startup specializes in tumor detection using transcriptional profiling on microarrays to obtain gene expressions.
What About The Other 265 Solutions?
While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence for your Proof of Concept (PoC), partnership, or investment targets. The 5 computer vision startups showcased above are promising examples out of 270 we analyzed for this article. To identify the most relevant solutions based on your specific criteria and collaboration strategy, get in touch.
