Izotropic Corporation announced it has entered into an agreement with Johns Hopkins University School of Medicine (JHU) to develop image reconstruction software (deep machine learning algorithms) to further improve the image processing performance of Breast CT while minimizing computational burden.JHU is recognized as a world leader in the development of image processing machine learning algorithms. The development will be led by Dr. Alejandro Sisniega-Crespo2, research Associate in JHU's Department of Biomedical Engineering and an expert in tomographic reconstruction methods, in collaboration with IzoView Founder and Company Director Dr. John Boone and others from the University of California Davis. Izotropic expects the collaboration will result in a novel set of learning-based approaches for accurate identification and characterization of breast pathologies.Izotropic is working to bring breakthrough developments in methods integrating data-based machine learning approaches to reduce noise and image biases with the preservation of the intrinsic spatial resolution of the IzoView system. Combining the true 3D high-resolution nature of IzoView breast CT with the expected excellent soft-tissue contrast provided by there construction methods, IzoView will offer an outstanding platform for the development and implementation of a novel set of learning-based approaches for accurate identification and characterization of breast pathologies. Software development is underway and will integrate into the fabrication of the Company's initial IzoView clinical study units. Clinical study units will include an enhanced product design and performance improvements for added usability to increase competitive advantages, a broadened product offering, and attract a larger target market.