Cardiophotonics develops non invasive blood monitors used to detect cardiac arrhythmia and dehydration

Mercator MedSystems has developed a broad-based therapeutic platform that allows clinicians to accurately and efficiently deliver drugs and biologics such as stem cells to tissues deep in the body, treating the root cause of significant medical conditions. The company utilizes its family of Micro-Infusion Catheters for targeted treatments via the vascular system, including peripheral artery disease (PAD) and resistant hypertension (HTN); and via the bronchial tree, including malignant airway obstruction secondary to lung cancer. The company's 510(k)-cleared and CE-Marked Cricket and Bullfrog Micro-Infusion Catheters are vascular-access systems that are able to inject drugs, genes, and cells safely through vessel walls into deep tissues without major surgery.

Mitomics, formerly Genesis Genomics, is developing molecular tests based on the mitochondrial genome in order to improve clinical insight and therapeutic decisions that affect patients worldwide. Leveraging its insights into the role of mitochondrial DNA (mtDNA), the company is developing a portfolio of molecular tests addressing significant unmet needs in oncology, including those related to prostate, breast, lung and skin cancers, and other disease states. The unique structural and functional characteristics of mtDNA make it a highly attractive system for biomarker discovery, early disease detection, monitoring, risk assessment and therapeutic targeting.

Kjaya is a company that received a SBIR Phase I grant for a project entitled: Semi-Autonomous Adaptive Neural and Genetic Segmentation of Medical Images. Their Phase I project will implement a physician-assisted, real-time adaptive system for the segmentation of anatomical structures in 3D medical image data. Medical image segmentation seeks to change the representation of an anatomical structure, making it more easily analyzed. Because of the extreme variability of these structures in biological systems, current idiosyncratic manual methods currently in use are tedious, time consuming, and error prone. Image segmentation cannot in general be programmatically solved. The proposed system is a Neural Network (NN) based adaptation of the individual data using parallel Graphics Processing Units (GPUs) and coupled with a Genetic Algorithm (GA) based adaptation across GPU cores. The system will build a diagnostically useful segmentation of the anatomical feature within seconds from an area of interest outlined by a physician using a Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scan. Fast growth in medical imaging overwhelms available diagnosticians. An intuitive and inexpensive system to quickly and accurately deliver diagnostic relevant segmentation of medical images offers tremendous commercial value. Currently, each scan requires approximately 50 minutes of manual preparation. The diagnosis and treatment of an estimated 20 percent of diseases benefit from medical imaging. Newer scanning technologies have increased in resolution, but such techniques have not made segmenting easier or faster. The proposed method will enable more diagnostics to be done with the quality controlled directly by physicians.

Knoesis seeks to develop bio-analytical hardware and reagents enabling cost-effective clinical diagnostics. The vision of the company is to allow everyone affordable access to rapid and specific diagnostic healthcare knowledge. Knoesis' first application is an immunosensor for the detection of latent tuberculosis infection.

UroCor Labs aims to provide a menu of diagnostic services to assist in detecting, diagnosing, treating and managing prostate cancer, bladder cancer, kidney stones, and other complex urologic disorders.