Medical imaging is the technique and process of creating visual representations of the interior of a body for clinical analysis and medical intervention. As this technology develops, clinicians are able to see and interpret more about inside bodies than ever before, including using artificial intelligence to bring faster diagnosis and treatment. The demand for cheaper, portable, and miniature versions of clinical image analysis tools is rising, especially in developing economies. According to a Siemens article “Great Growth Potential for Medical Imaging Systems,” sales of medical imaging equipment in India are expected to increase from $550 million in 2011 to around $1.27 billion by 2018. Furthermore, according to research done at Harvard Medical School, a patient’s hospital stay is reduced by one day for every $385 spent on medical imaging equipment, which could save approximately $3,000 per patient.
Yvon Julé, the Chief Science Officer and Co-Founder of Biocellvia, a French company that performs completely automated digital image analysis for preclinical disease model says, “Throughout my career, I have witnessed numerous failures in the drug development process, and unfortunately many inactive molecules move into the clinical stage based on inadequate data. I then understood in the 1990s the immense interest and potential in digital imaging, especially its application in the preclinical phase to better assess the efficacy of molecules.Today, everyone in the industry recognizes the benefits and importance of applying and integrating digital technologies in their research and development, such as machine learning image analysis. Those who fall behind the curve will be at a big disadvantage.” Julé plans to attend the 2018 BIO International Convention in Boston beginning June 1.
Sanjay Prabhu, the founding director of the Advanced Image Analysis lab at Boston Children’s Hospital says, “Imaging of the human anatomy is still largely qualitative in that most imaging studies are accompanied by descriptive reports. Very few areas like cardiac and vascular imaging and neuroimaging studies to some extent include numbers in reports. Having access to rapid and accurate image analysis software with machine learning and artificial intelligence built in for both normal subjects and patients will change the way we view disease states and measure responses to drug and non-drug treatments.”
Here are the Top 5 Clinical Image Analysis Startups in the US:
Nanotronics Imaging is an Ohio based startup that has raised a $30M Series D that was announced on October 3, 2017. The company develops advanced AI powered microscopes that can detect patterns and create new algorithms, in order to provide their technology to health manufacturing sectors. The company combines optical microscopy, computational super-resolution, artificial intelligence, and robotics while reducing costs in their patented microscope system entitled nSPEC® for leading manufacturing companies globally. Furthermore, their software is able to detect patterns and classify them intelligently at increased resolutions with minimal user training, which has historically been done manually. The company’s technology has been able to detect defects with as little as ten sample images, and then create the algorithm to begin classifying a new defect type. The company hopes to release a general artificial intelligence solution that will require virtually zero training data in 2018.
VoxelCloud is a Los Angeles, California based startup that has raised a $15M Series A, which was announced on October 2, 2017. The company uses AI and cloud computing medical image analysis algorithms to help doctors make more informed clinical decisions in the diagnosis of lung cancer, retinal diseases, and coronary heart disease. Their AI analysis of medical images is validated and annotated by experts and real world training data. Their cloud computing technology on the internet allows clinicians access to vast amounts of data insights in their own offices, integrating with existing clinical workflows. Their technology has been incorporated into medical centers and clinics across the nation, giving direct support to healthcare providers. The company also partners with established vendors and third party developers to develop new applications within the API.
NeuroVision Imaging is a Sacramento, California based startup that has raised an $11.2M Series C, that was announced on May 2, 2018. NeuroVision is conducting clinical trials that are proving the efficacy of diagnoses of neurodegenerative diseases through image analysis of the eyes. One sign of Alzheimer’s disease is an accumulation of amyloid beta plaque in the brain. This plaque also builds up in the retina, which allows for better and faster diagnoses through clinical image analysis that link the structure and characteristics of the plaque to the onset of Alzheimer’s. The company’s technology is being used in several clinical trials globally that seek to use ophthalmological imaging to prove the link between the buildup of this plaque in the retina to solid diagnoses. NeuroVision gives their image analysis tools to clinical trials all over the world, including Janssen Research & Development LLC, a pharmaceutical company of Johnson & Johnson. NeuroVision also gives clinical trials their data aggregation services, analysis, biostatistics, machine learning algorithms of the images in order to help further research and fight against neurodegenerative diseases.
Techcyte is a Utah based startup that has raised a $4.3M Series A that was announced on January 18, 2018. The company uses machine learning to empower digital diagnostics in pathology. Their decision to create digital tools for pathology arose from a demand for pathologists against an exponentially growing world population. Their cloud based technology helps pathologists identify diseases accurately as glass slides are uploaded to the computer and are then automatically analyzed by machine learning using algorithms to identify suspect cells. While pathologists would traditionally, have to analyze and identify these suspect cells manually before machine learning analysis and identification, their AI solution helps reduce mistakes, improve efficiency, and cut costs.
Ben Cahoon, the Chief Operating Officer of Techcyte says, “Techcyte’s deep learning image analysis platform reads images from any quality whole slide scanner, analyzes and returns the results back to the medical technician or pathologist. This solution is currently being used to evaluate everything from blood to fecal to pap smears around the world. The combination a pathologist’s expertise and Techcyte’s image analysis returns quicker, more accurate results to patients while reducing costs for labs and hospitals.”
AnatoMotion is an Austin, Texas based startup that has raised a $225K Seed Round that was announced on July 1, 2017. They are a dental motion analysis technology company with products in the development stage. The company has developed imaging technology that analyzes the bites of patients while they sleep for better insight into dental bite issues that arise from sleep apnea, grinding teeth, and temporomandibular disorder problems. Their IoT technology called e-Bite is a smart wearable that give dentists and patients greater ability to interpret how these dental issues are exacerbated while sleeping, as well as an individualized functional digital model. The smart sensors within the mouth are activated by movement to give 3D images within the mouth.
Leah D’Sa is a Junior studying Writing, Literature, and Publishing at Emerson College. She is currently a copyeditor for the school newspaper the Berkeley Beacon as well as Poetry Editor for the literary magazine the Emerson Review. She is looking to begin her career with health technology writing as she seeks to combine her lifelong love of writing and science.
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