Izotropic Signs Agreement with Johns Hopkins University School of Medicine to Develop Deep Machine Learning Algorithms for IzoView Breast CT

September 21, 2021 8:00 AM EDT | Source: Izotropic Corporation

Vancouver, British Columbia--(Newsfile Corp. - September 21, 2021) - Izotropic Corporation (CSE: IZO) (OTCQB: IZOZF) (FSE: 1R3) ("Izotropic" or the "Company"), a Company commercializing a dedicated breast CT (computed tomography) imaging platform, IzoView, for the more accurate detection and diagnosis of breast cancers, announced today 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 burden1.

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, a 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 the reconstruction 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.

IzoView produces high-resolution breast images in true 3D and is ideal for imaging patients with dense breast tissue. A single 10-second scan acquires approximately 500 images without painful breast compression or continual technician breast handling, providing a more comfortable patient experience with low radiation dose levels.

In addition to improved detection capabilities, Izotropic anticipates IzoView's higher resolution 3D images could provide more accurate margin analysis (viewing edges of a tumor), lesion characterization (determining the qualities of an abnormality), and higher spatial resolution (the imaging ability to differentiate between internal breast structures).

Dr. John McGraw, CEO

For investor relations inquiries, contact:

James Berard
Email: jberard@izocorp.com
Cell: 778-228-2314
Toll Free: 1-833-IZOCORP ext.1

About Izotropic Corporation

Izotropic Corporation is the only publicly traded company commercializing a dedicated breast CT imaging platform, IzoView, for the more accurate detection and diagnosis of breast cancers. To expedite patient and provider access to IzoView, Izotropic's initial clinical study intends to demonstrate superior performance of diagnostic breast CT imaging over diagnostic mammography procedures and will initiate in Q2 2022. In follow-on clinical studies, Izotropic intends to validate platform applications including breast screening in radiology, treatment planning and monitoring in surgical oncology, and breast reconstruction and implant monitoring in plastic and reconstructive surgery.

More information about Izotropic Corporation can be found on its website at izocorp.com and by reviewing its profile on SEDAR at sedar.com.

Forward-Looking Statements

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1 The amount of resources required to run the algorithm.
2 Dr. Sisniega-Crespo's bio can be found at https://www.bme.jhu.edu/people/faculty/alejandro-sisniega-crespo/

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