Medical imaging, by definition, refers to a number of completely different applied sciences used to view the human physique to diagnose, monitor, or deal with medical situations. Every sort of know-how offers completely different details about the space of the physique being studied or handled, associated to attainable illness, damage, or the effectiveness of medical remedy. Beginning with the microscope, the place cells had been considered for the first time, medical imaging has advanced dramatically over the years. It has reached new frontiers regarding each prognosis of ailments in addition to planning and monitoring remedy efficacy by utilizing the utility of synthetic intelligence (AI). “The medical imaging market is worth USD 34 billion and is expanding, owing to the increased demand for remote diagnostics due to COVID-19. Another driving force is the rapidly growing geriatric population. There is a shortage of radiologists, neurologists, and psychiatrists, so rapid and objective medical diagnostics are essential for healthcare systems,” says Dr. David H. Nguyen, Ph.D., CEO and Co-Founder, BrainScanology.

Dr. Nguyen is a computational biologist who invented an algorithm to measure form with out measuring space or quantity. He has written 5 novel algorithms to quantify “randomness” in the structure of tumors (ww.TSG-Lab.org), an strategy nobody else has computationally conceived earlier than. In 2020, Dr. Nguyen established BrainScanology, Inc, collaborating together with his former analysis intern, Harini Kumar, MBA, who’s skilled in each scientific and shopper analysis with a profound understanding of the present market house, key gamers and initiatives, and the total enterprise local weather. Now the staff is engaged on launching BrainScanology’s software program, known as ShapeGenie (www.ShapeGenie.internet), which may measure shapes in ways in which Deep Studying methods in the discipline of laptop imaginative and prescient can’t. It permits for the re-inclusion of human creativity in measuring organic shapes that correlate with illness and illness. “Deep Learning requires the user to define ‘ground truth’ categories, meaning what is considered healthy and what is considered diseased. ShapeGenie, on the other hand, helps the user discover new ground truth categories hidden from the naked eye and Deep Learning. These new categories can then be taught to Deep Learning for rapid detection,” explains Dr. Nguyen.

ShapeGenie permits the person to specify which organ shapes to measure. The outcomes are extremely interpretable, permitting the doctor to elucidate to a affected person what options had been measured and why. “Deep Learning models struggle with interpretability because they are excellent at distinguishing between healthy and diseased patients but do so in a way humans do not comprehend,” provides Dr. Nguyen.

 Dr. David H. Nguyen & Harini Kumar

BrainScanology: What Does It Do?

BrainScanology, Inc is a know-how startup creating ground-breaking form evaluation software program that doesn’t require space or quantity measurements. It develops software program that enables medical doctors to measure advanced organic shapes to higher perceive ailments imaged by MRI, CT, X-ray, and ultrasound. Dr. Nguyen says, “We are developing our software as a SaaS product available for all fields of science to do shape analysis: from agricultural engineering to home appliance design, to medical diagnostics, to aerospace engineering.”

BrainScanology’s ShapeGenie software program is scheduled to launch a minimal viable product (MVP) model in January 2023. ShapeGenie has already offered early adopters with consulting providers to check its efficacy for his or her analysis. “ShapeGenie will be a cloud-based software (a “SaaS service”) to which customers will be capable of subscribe, add their pictures, after which obtain the evaluation outcomes. Along with a ShapeGenie license, clients can buy consulting providers from BrainScanology workers on methods to finest apply ShapeGenie to particular analysis questions,” shares Harini. BrainScanology additionally presents a service for creating machine studying fashions that predict particular ailments primarily based on buyer picture knowledge.

BrainScanology distinguishes itself from opponents in the market because it has filed a PCT patent utility for the use of the LCPC Remodel in medical diagnostics starting from the mobile to the organ to the organismal degree (instance: finger shapes). Dr. Nguyen states, “While we can build in traditional measures of area and volume in our software, our competitors cannot build in the LCPC Transform into their software.”

BrainScanology additionally collaborates with particular person tutorial labs or medtech corporations. Companions profit from entry to its form evaluation and analysis experience. That is helpful for creating customized machine studying fashions and making use of for analysis grants. The corporate additionally offers free pilot research to shoppers to exhibit that they’ll measure what different methods can’t. Dr. Nguyen provides, “They compare our results with their previous results to see ShapeGenie’s unmatched level of precision and efficacy.”

Massive Choices Outcome from Massive Incidents

The concept of making BrainScanology got here after a collection of tragic incidents in Dr. Nguyen’s life. It began with the dying of Dr. Nguyen’s shut school pal, named Thuan Trinh, who took his personal life attributable to bipolar dysfunction. Throughout the years of battle that led to Trinh’s dying, Dr. Nguyen was going by way of deep despair in his personal life. At Trinh’s funeral, he made a promise to do one thing about bipolar dysfunction. Years after that, Dr. Nguyen’s favourite highschool biology trainer, Duane Nichols, died of an aggressive type of colon most cancers that had recurred thrice. To commemorate his former mentor, who impressed him to review science in school, Dr. Nguyen spent many sleepless nights inspecting histopathology pictures of colon polyps to derive a statistical methodology to measure the subtleties of advanced organic shapes.

After per week of scribbling and crumpled paper, the Linearized Compressed Polar Coordinates (LCPC) Remodel was based to honor Nichols at his memorial service. Informally, the LCPC Remodel was dubbed the “Nguyen-Nichols Transform.” Nguyen finally realized that the LCPC Remodel might be used to quantify mind folds and thus measure the distinction between wholesome and diseased brains. Thus was born the idea of BrainScanology, David Nguyen and Harini Kumar’s first startup.

Distinctive Efficiency Results in Hanging Progress

BrainScanology is just two years outdated, but it surely already has early adopters from the world’s high analysis establishments, with extra becoming a member of each week. Harini highlights, “Once our SaaS software is released in January of 2023, the number of subscribers will skyrocket because we will offer free subscriptions under a freemium model that allows users to test our software at a limited capacity.” The Nationwide Science Basis invited the BrainScanology staff to use for an SBIR grant for his or her machine studying mannequin that detects Alzheimer’s illness by analyzing mind MRIs. “This Alzheimer’s model will likely be our first go-to-market clinical decision support product for the USA in the coming years,” added Harini.

Offering Recognition to Encourage Workers

BrainScanology acknowledges its staff, even when they’re interns. This manifests as co-authorship of shows and stories. In addition they maintain common conferences to maintain the staff abreast of everybody’s progress and contributions. Nguyen mentions, “As a small company, everyone’s contribution has a positive impact, so we make sure that everyone understands this, which helps them feel ownership of their work.” Particular person interns may pursue unbiased tasks over the summer season, permitting them to pursue completely different subjects primarily based on the firm’s know-how.

Poised to Uncover Unanticipated Subtypes of Illnesses in the Future

BrainScanology is getting ready to find unknown subtypes of many ailments in the coming years. Harini factors out, “Once we get our SaaS software into the hands of many scientists, it will only be a matter of time when other labs make the same groundbreaking discoveries that we have been making over the past two years.” They’re taking their know-how on to African international locations to develop race- and sex-specific medical diagnostic AI in collaboration with native clinics. That is known as the Medical AI for African Nations Initiative, or MAfoAN (“mah-foh-anh”) Initiative (https://africamedicalai.wordpress.com/). “Our technology is amazing. We don’t think that other countries should wait for the U.S. FDA to approve our technology before those countries can start benefiting from it if they have the imaging data and are willing to share it now,” added Harini.

Planning a International Footprint

Harini says, “Because we measure the shape and not signal intensity, our disease-specific machine learning models can work on images from older MRI machines and CT scans that provide low-resolution images. For example, our Alzheimer’s model is based on the shape of the lateral ventricles in the brain, which is a liquid space that appears obviously different than brain tissue in MRI scans.” Since low-resolution CT scans clearly present the form of the lateral ventricles, their Alzheimer’s detection mannequin may match nicely with a low-resolution CT scan, permitting potential Alzheimer’s sufferers simpler entry to mind imaging. CT scans are cheaper and sooner than MRIs, each of that are benefits.

The software program developed by BrainScanology is more practical at detecting organ form variations than space and quantity variations, which can be utilized for machine studying fashions that may be utilized throughout completely different populations of individuals. “This applies to many psychiatric diseases for which the current method of diagnosis is highly subjective and prolonged. We can cut diagnostic wait times by 10-50X,” underlined Dr. Nguyen.

Their software program can generate diagnostic fashions primarily based on ultrasound sonogram pictures, making it superb for distant and rural areas. Since ultrasound pictures are so low in decision, any machine studying fashions developed for MRI pictures is not going to work on ultrasound pictures. “However, this is not a problem for our technology if the shape of interest is visible in both an MRI and a sonogram. The science of machine learning and diagnostics is an iterative, self-correcting process that takes time to optimize, so now is the time to start,” concludes Dr. Nguyen.

For Extra Information: https://www.brainscanology.com/

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The Obsessed Guy
Hi, I'm The Obsessed Guy and I am passionate about artificial intelligence. I have spent years studying and working in the field, and I am fascinated by the potential of machine learning, deep learning, and natural language processing. I love exploring how these technologies are being used to solve real-world problems and am always eager to learn more. In my spare time, you can find me tinkering with neural networks and reading about the latest AI research.

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