Perceptronix Medical, Inc.

Alpineon D.o.o.

Perceptronix Medical, Inc. and British Columbia Cancer Agency

Mario Zganec

Branko Mihael Palcic

Gary William Ferguson

Margareta Flezar

Jaka Lavrencak

Calum E MacAulay

David M Garner

Jerneja Zganec Gros

Alexei K Doudkine

Marija Us-Krasovec

Gros Jerneja Zganec

Active 3D triangulation-based imaging comprises steps of: temporally modulating a radiant flux of a lighting unit beam by a binary modulation signal (ms); illuminating a scene (S), which is illuminated by an ambient lighting (AL), by said modulated lighting unit beam (mlub); splitting a ray (ir) imaging a scene point (SP) into two separate imaging rays (ir, ir); said first separate imaging ray (ir) forming an image in a first image sensor (is); temporally modulating a radiant flux of the second separate imaging ray (ir) by the modulation signal (ms) and said modulated second separate imaging ray (ir) forming an image in a second image sensor (is); normalizing a first scene image being an image of all points of the scene (S) formed in the first sensor (is) and a second scene image formed in the second sensor (is); and subtracting the first normalized scene image from the second normalized scene image. The proposed imaging using the random binary modulation signal distinguishes itself by a resistance to intentionally or unintentionally caused interferences. Hence the application is especially advantageous in machine vision appliances provided in an autonomous mobile robot or vehicle. The low radiant flux of the modulated lighting unit beam makes it possible to reduce the input power to a light source of the lighting unit hereby saving the energy and reducing lighting source costs.

Active 3D triangulation-based imaging method and device

Computer programs, systems and the like related to processing, segmenting and feature normalizing digital images. The images are of cells and the methods are useful for the detection of malignancy-associated changes (MAC) in cells, which can be used for the detection of cancer. The programs and methods detect cancer in one tissue by detecting MAC in another tissue, such as associated tissues or non-associated tissues. Examples of associated tissues include nipple aspirates or ductal washings to detect breast cancer, and sputum or bronchial lavage to detect lung cancer. Examples of non-associated tissues include buccal mucosa to detect lung or breast cancer.

Computerized methods and systems related to the detection of malignancy-associated changes (MAC) to detect cancer

The present invention provides a simple, inexpensive apparatus for and method of capturing biological or other material from sample suspensions on a collection surface and for depositing captured material on a receiving surface, such as a microscope slide, for observation and analysis. Accordingly, cytological material may be deposited in near mono-layers for the detection of disease. In one embodiment of the present invention, density gradients of material are captured and deposited, thus providing a desired range of concentrations for examination. In another embodiment multiple depositions or multiple slides may be made from the same sample suspension. The method and apparatus to exploit this new method are both presented for various applications. The dimensions of material captured and deposited may be controlled and used in conjunction with microscope slides that confine material to specific regions of interest.

Filter devices for depositing material and density gradients of material from sample suspension

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Golnik, Slovenia

Mario Zganec