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Spectral Image

Founded Year



Series A | Alive

Total Raised


Last Raised

$5M | 15 yrs ago

About Spectral Image

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.

Headquarters Location

1 Corporate Center

Tampa, Florida, 33607,

United States


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Spectral Image Patents

Spectral Image has filed 5 patents.

The 3 most popular patent topics include:

  • Imaging
  • Medical imaging
  • Rare diseases
patents chart

Application Date

Grant Date


Related Topics




Spectroscopy, Medical imaging, Rare diseases, Remote sensing, Imaging


Application Date


Grant Date



Related Topics

Spectroscopy, Medical imaging, Rare diseases, Remote sensing, Imaging



Spectral Image Frequently Asked Questions (FAQ)

  • When was Spectral Image founded?

    Spectral Image was founded in 2007.

  • Where is Spectral Image's headquarters?

    Spectral Image's headquarters is located at 1 Corporate Center, Tampa.

  • What is Spectral Image's latest funding round?

    Spectral Image's latest funding round is Series A.

  • How much did Spectral Image raise?

    Spectral Image raised a total of $5M.

  • Who are the investors of Spectral Image?

    Investors of Spectral Image include Biomark Capital.

  • Who are Spectral Image's competitors?

    Competitors of Spectral Image include MedShape, Upromise, Stage I Diagnostics, Micrima, Oncoscope and 13 more.

Compare Spectral Image to Competitors


MediSpectra, Inc. is a medical device company developing optical detection technology for enhanced accuracy and real-time results in the detection of cancer and other human tissue abnormalities. The technology is based on multimodal optical interrogation of tissue with light. Specifically, a combination of native fluorescence and white light backscatter spectroscopies are coupled with video imaging methods to more accurately detect tissue abnormalities. nnThe company's first product, the LUMA Cervical Imaging System, was designed and developed to improve the detection of high-grade pre-cancerous cervical abnormalities that have the potential of becoming invasive cancer. The LUMA product is intended for use as an adjunct to colposcopy in identifying high grade disease (CIN 2/3+) in patients referred to colposcopy with an ASCUS, LSIL or HSIL+ cervical cytology test result. n

Micrima Logo

Micrima is a Bristol-based company developing a safe, low-cost system to improve the detection of breast cancer. The imaging system captures high-resolution, 3D images through the use of harmless radio waves. The safe, low-cost system enables women of all ages to be screened for breast cancer in GP surgeries, or alternative high street locations, with results that are now comparable with traditional X-ray mammograms.


Diamics, Inc. is a medical device and diagnostics company. The company is developing, manufacturing, and marketing cost effective cancer diagnostic systems that will increase long-term cancer survival rates through early detection.

Forth Photonics

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.


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.

CT Atlantic

CT Atlantic is an early stage company focused on the identification and development of human oncology

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