McMarvin’s mission is to provide the healthcare industry the tools they need to make the next leap in patient care.

The demand for AI-based solutions are continuously increasing, outpacing the supply of qualified radiologists and stretching them to produce more output, without compromising patient care. Only by adopting new technologies like Artificial Intelligence and Machine Learning that significantly enhances the capabilities of radiologists/physicians, can this crisis be mitigated.

McMarvin is empowering healthcare with its revolutionary AI services which helps health providers manage the ever-increasing workload without compromising quality.


McMarvin works with millions of imaging and correlated clinical records to build state-of-the-art algorithms that automatically detect medical conditions faster, for numerous findings in parallel.

Over the next few years we expect to explore several untouched areas of automated findings and insights to help radiologists provide more effective, accurate outcomes – faster, without compromising the quality of care.


1. Brain Tumor Segmentation

To help doctors more effectively analyze and monitor tumors, McMarvin’s AI experts have developed a robust deep learning-based solution that uses 3D MRI and CTs to automatically segment tumors. Radiologists/Physicians can easily go through the segmented tumor’s boundary to understand about the shape, size, and orientation.

Automated segmentation of brain tumors can save time and lives. It provides an accurate reproducible solution for further tumor analysis and monitoring.

2. Breast Cancer Detection

McMarvin has developed an artificial intelligence model that could accurately detect breast cancer in screening mammograms with greater accuracy, fewer false positives, and fewer false negatives than human experts.

Reading X-ray images is a difficult task, even for experts, and can often result in both false positives and false negatives. In turn, these inaccuracies can lead to delays in detection and treatment, unnecessary stress for patients and a higher workload for radiologists who are already in short of supply. AI-based tools can assist the oncologist to save time and save the lives of cancer patients. We’re looking forward to working with our partners in the coming years to translate our machine learning research into tools that benefit clinicians and patients.

3. Lung Nodules Detection

A nodule is a small lump of tissue that is not normally present in the lungs. Finding nodules is a classic "needle-in-a-haystack" problem. This is because nodules are usually tiny, and many other structures like blood vessels and scars can look like them at first glance. There are a range of nodule features that radiologists use to determine which nodules might be cancerous.

The most commonly used system is the Fleischner criteria, which only consider the size and number of nodules and the presence of risk factors like smoking. Other systems are more complicated and include the shape and location of the nodules.

The artificial intelligence being developed for medical use is typically complicated pattern matching: An algorithm is shown many many medical scans of organs with tumors, as well as tumor-free images, and tasked with learning the patterns that differentiate the two categories.

4. Respiratory Diseases

With approximately 2 billion procedures per year, chest X-rays are the most common imaging examination tool used in practice, critical for screening, diagnosis, and management of diseases including pneumonia. However, an estimated two-thirds of the global population lacks access to radiology diagnostics.

With automation at the level of experts, we hope that this technology can improve healthcare delivery and increase access to medical imaging expertise in parts of the world where access to skilled radiologists is limited.

McMarvin’s AI-based algorithm can detect respiratory diseases like Pneumonia, Pneumothorax, Coronavirus, TB and other flu-based diseases within minutes.

5. Diabetic Retinopathy

Immediate, Fully-automated, On-site Diabetic Retinopathy Screening

Diabetic eye diseases are a leading cause of blindness around the world, and McMarvin’s research team is developing deep learning solutions that could enhance the ease, efficiency, and accuracy of diagnosing diabetic retinopathy, including at different stages and with diabetic macular edema.

McMarvin is developing a technology for autonomous detection of diabetic retinopathy, trained on more than half-million patients and nearly two million retinal images globally.

McMarvin Screening System is developing in-clinic, real-time diabetic retinopathy (DR) screening possible for primary care practices, diabetes centers and optometric offices by allowing physicians to quickly and accurately identify referable DR patients during a diabetic patient’s regular exam.

6. Orthopedic Surgery Assistant solution

McMarvin’s solution provides powerful new technology that can identify vertebral compression fractures in an effort to tackle osteoporosis.

We are working with the top orthopedic surgeon “Dr.Sreedhar” Retd. Additional Director, All india institute of Physical Medicine and Rehabilitation (AIIPMR, Govt of india), and building innovative solutions for bone density, surgeries, etc.

Fast Diagnosis:
Complete screening of various fractures and other bone lesions in the chest within 20 seconds, including rib, clavicle, scapula, vertebrae, sternum and other structure labels, with location information on fractures and other bone lesions.

Accurate identification of fractures and suspected fractures, bone destruction, bone metastases, bone tumors, postoperative lesions, and more.