Amicas

Atonomics develops a point of care diagnostic device based on an electro-mechanical concept. This technology changes the way that DNA and antibodies are used in point of care diagnosis.

Tensys Medical Tensys has developed a continuous, non-invasive blood pressure monitoring technology for cardiac output assessment that is easy to administer and comfortable for the patient. San Diego, CA.

Forth Photonics is a medical device company that designs, develops, manufactures and markets imaging systems for the non-invasive, in-vivo detection of cancerous and pre-cancerous lesions. Forth Photonics aims to help medical practitioners to improve patient care by incorporating advanced biophotonics and optical molecular imaging technologies to assist in early detection, diagnosis and monitoring.

Nanocrystal Imaging Corporation (NIC) was founded in October 1997 to exploit some of NCT's discoveries in the creation of high quality digital x-ray images. This has been a major objective of the medical imaging industry during the last decade. Digital x-ray imaging systems developed to date by other manufacturers do not produce images with sufficiently high resolution and contrast. After a 4-year effort, NIC has developed patented products and processes which can provide a reliable platform to achieve high quality digital x-ray imaging. The first of NIC's products for commercial use is addressed to the dental imaging market, and will be marketed by mid 2003. Products addressing other market will be available in successive years. in the creation of nano-sized luminescent particles with light output equivalent to that of commercial phosphors 1000 times larger

a privately held, early stage medical device company focused on the development of imaging technology for biomedical use. The company is currently in stealth-mode and not disclosing the finer details of its technology until it secures necessary intellectual property rights. Spectral Image will initiate a pilot study of its technology at a premier medical facilities in 2008.

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.