We need a new technology for imaging the default (occult) condition of Dirofilariasis in humans. Ultrasound, MRI, and CT scans all fail to diagnose this disease, so we obviously need something new in order to prove this disease is present. The current Motion-Extraction prototype camera design has one major drawback in that it requires the filaria to actually cooperate during the exam in order to get any diagnostic evidence that the disease is present. There are of course techniques we can use (e.g. stimulants, or immune activation compounds) for doing this, but they may be somewhat unpleasant for the patient. It will however be sufficient to prove that the disease is present, and then to collect together a sufficient cohort of people to study, but it is obviously not the best clinical diagnostic device possible. Using our knowledge of basic physics we can definitely improve upon this.
A much better design is possible, by using a Gallium Arsenide (InGaAs) sensor camera, which would actually be capable of quantifying all the different chemical bonds in the various tissues of both the filaria and the surrounding human tissues, and then differentiating between them. Each wavelength of infra-red light will interact with different tissues according to the chemical composition of those tissues. For instance, the chemical signature of oxygenated verses non-oxygenated hemoglobin is different, and those will be vastly different than any muscular protein or carbohydrates found in the filaria. These other tissues should not be colocated in the exact same region unless there is an infection. By using multiple wavelengths of infrared light it should be possible to see exactly where the hemoglobin is and then look for the direct signature of the specific carbohydrates in the region where they should not otherwise exist.
The sensor required for this prototype is priced somewhere between 10,000-20,000 US dollars but otherwise the prototype for this will be essentially the same cost as the current Motion-Extraction design. The sensor is the major component required to build this new design but the software will be different.
This more sensitive InGaAs technology with a USB interface would allow the identification of a filaria even in a static situation, and thus this is a much better match for the clinical diagnostics environment. The advanced camera would process multiple images, each taken at different wavelengths (900nm-2000nm), and then the onboard CPU/AI processor could directly build a composite image of the invader from that image data. A clinician would only need to ask the patient to point to where they have felt the sensations in the past and the camera will do the rest. No motion required. Under the right circumstances a clear diagnosis of Dirofilaria might be near instantaneous.
Once we are able to determine what specific frequencies are required to properly differentiate between the tissues, it should be possible to build a low cost portable clinical diagnostic camera for putting out in the field for doctors to use and examine their patients.