We have designed and fabricated a 176×144-pixels (QCIF) CMOS image sensor for on-chip bio-fluorescence imaging of the mouse brain. In our approach, a single CMOS image sensor chip without additional optics is used. This enables imaging at arbitrary depths into the brain; a clear advantage compared to existing optical microscopy methods. Packaging of the chip represents a challenge for in vivo imaging. We developed a novel packaging process whereby an excitation filter is applied onto the sensor. This eliminates the use of a filter cube found in conventional fluorescence microscopes. The fully packaged chip is about 350 μm thick. Using the device, we demonstrated in vitro on-chip fluorescence imaging of a 400 μm thick mouse brain slice detailing the hippocampus. The image obtained compares favorably to the image captured by conventional microscopes in terms of image resolution. In order to study imaging in vivo, we also developed a phantom media. In situ fluorophore measurement shows that detection through the turbid medium of up to 1 mm thickness is possible. We have successfully demonstrated imaging deep into the hippocampal region of the mouse brain where quantitative fluorometric measurements was made. This work is expected to lead to a promising new tool for imaging the brain in vivo.
Image sensors with pulse modulation measurement scheme are fabricated for bioimaging and biosensing ap-plications. We designed pulse modulation photosensors, a 64×64-pixels image sensor for in vitro bioimaging, and a 176×144-pixels (QCIF) image sensor for in vivo bioimaging. We demonstrated the feasibility of the pulse modulation measurement scheme for biosensing applications. We obtained a dynamic range of 120dB and minimum sensing intensity level of 2nW/cm<sup>2</sup>. We also confirmed that 0.2% of intensity change is detectable at the minimum intensity region. An in vitro, on-chip imaging of a mouse hippocampus was successfully demonstrated. A sensor module for in vivo imaging is also developed.
We are exploring the application of pulse-frequency-modulation (PFM) photosensor to retinal prosthesis for the blind because behavior of PFM photosensors is similar to retinal ganglion cells, from which visual data are transmitted from the retina toward the brain. We have developed retinal-prosthesis vision chips that reshape the output pulses of the PFM photosensor to biphasic current pulses suitable for electric stimulation of retinal cells. In this paper, we introduce image-processing functions to the pixel circuits. We have designed a 16x16-pixel retinal-prosthesis vision chip with several kinds of in-pixel digital image processing such as edge enhancement, edge detection, and low-pass filtering. This chip is a prototype demonstrator of the retinal prosthesis vision chip applicable to in-vitro experiments. By utilizing the feature of PFM photosensor, we propose a new scheme to implement the above image processing in a frequency domain by digital circuitry. Intensity of incident light is converted to a 1-bit data stream by a PFM photosensor, and then image processing is executed by a 1-bit image processor based on joint and annihilation of pulses.
The retinal prosthesis vision chip is composed of four blocks: a pixels array block, a row-parallel stimulation current amplifiers array block, a decoder block, and a base current generators block. All blocks except PFM photosensors and stimulation current amplifiers are embodied as digital circuitry. This fact contributes to robustness against noises and fluctuation of power lines. With our vision chip, we can control photosensitivity and intensity and durations of stimulus biphasic currents, which are necessary for retinal prosthesis vision chip. The designed dynamic range is more than 100 dB. The amplitude of the stimulus current is given by a base current, which is common for all pixels, multiplied by a value in an amplitude memory of pixel. Base currents of the negative and positive pulses are common for the all pixels, and they are set in a linear manner. Otherwise, the value in the amplitude memory of the pixel is presented in an exponential manner to cover the wide range. The stimulus currents are put out column by column by scanning. The pixel size is 240um x 240um. Each pixel has a bonding pad on which stimulus electrode is to be formed. We will show the experimental results of the test chip.
We have developed a CMOS vision chip, an image sensor with pixel-level signal processing, to replace photoreceptor cells in the retina. In this paper, we describe a pixel-level signal processing, which is to control on the stimulus waveform and the amount of the electrical injection charge.
Our CMOS vision chip is an array of a pixel, which consists of a photo detector, a pulse shaper, and a current stimulus circuit. The photo detector circuit generates a pulse frequency modulated (PFM) pulse, which frequency is proportional to the intensity of the incoming light. The PFM photo detector is also modified to restrict the maximum frequency of PFM pulse signal for safety neural stimulation.
The PFM pulse signal should be converted into suitable waveform for efficient neural stimulation. We have employed a pulse shaper to generate one stimulus pulse from one PFM pulse. The pulse parameters (i.e., pulse duration, polarity, etc) of the output pulse signal are controlled by the external signal.
For the electrical neural stimulus, the stimulus intensity is given by the amount of the electrical injection charge. The amount of the injection charge should be enough to evoke a phosphene but should be low to avoid the damage of the retinal tissue caused by the excess charge injection. In our prototyped CMOS vision chip, the stimulus current amplitude is used to control the amount of charge. The 6-bit binary-weighted digital-to-analog converter (DAC) with 2μA resolution is used to control the stimulus current amplitude.