MEMS microscope head speeds cancer detection

Munich, Germany-- A microscopic image sensor, fitted in an endoscope, is being developed for in vivo cancer diagnosis, to speed up the detection of tumors in a minimally invasive surgical operation.

Munich, Germany-- A microscopic image sensor, fitted in an endoscope, is being developed for in vivo cancer diagnosis, to speed up the detection of tumors in a minimally invasive surgical operation.

Research scientists at the Fraunhofer Institute for Photonic Microsystems IPMS in Dresden have developed a microscope head with an 8-mm diameter to optically resolve and magnify tissue cells measuring 10 to 20 µm. The scientists envision that the microelectromechanical system (MEMS) microscope head will eliminate the need for biopsies. Diagnosis in real time would enable doctors to decide on the necessary course of treatment more quickly.

"In classic endoscopy using macroscopic imaging, the job can be done by CCD or CMOS image sensors, as used in digital cameras and cell phones," says Dr. Michael Scholles, business unit manager at the IPMS. "For endomicroscopy, however, MEMS-based image sensors are highly advantageous because they can magnify even the smallest object fields, such as cells, without the need for a large lens. We have combined the sensor with a microscanner mirror to achieve the required resolution of 10 µm, and can,therefore, massively magnify the tiniest structures."

As far as how the system functions, the laser itself is located in the operating theater. The laser light is conducted via a transmitting fiber to the microscanner mirror fitted in the tip of the endoscope. This deflects the laser beam and illuminates the suspicious tissue specifically. A glass-fiber bundle in the tip of the endoscope transmits the reflected light to the external sensor, which receives a signal containing the image information. A detector precisely measures the position of the scanner mirror, indicating which area of the scene is being illuminated at the specific point in time. A 2-D image can thus be completely reconstructed by combining the position and image sensor signals.

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