2 resultados para Clinical diagnosis

em CaltechTHESIS


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Optical microscopy is an essential tool in biological science and one of the gold standards for medical examinations. Miniaturization of microscopes can be a crucial stepping stone towards realizing compact, cost-effective and portable platforms for biomedical research and healthcare. This thesis reports on implementations of bright-field and fluorescence chip-scale microscopes for a variety of biological imaging applications. The term “chip-scale microscopy” refers to lensless imaging techniques realized in the form of mass-producible semiconductor devices, which transforms the fundamental design of optical microscopes.

Our strategy for chip-scale microscopy involves utilization of low-cost Complementary metal Oxide Semiconductor (CMOS) image sensors, computational image processing and micro-fabricated structural components. First, the sub-pixel resolving optofluidic microscope (SROFM), will be presented, which combines microfluidics and pixel super-resolution image reconstruction to perform high-throughput imaging of fluidic samples, such as blood cells. We discuss design parameters and construction of the device, as well as the resulting images and the resolution of the device, which was 0.66 µm at the highest acuity. The potential applications of SROFM for clinical diagnosis of malaria in the resource-limited settings is discussed.

Next, the implementations of ePetri, a self-imaging Petri dish platform with microscopy resolution, are presented. Here, we simply place the sample of interest on the surface of the image sensor and capture the direct shadow images under the illumination. By taking advantage of the inherent motion of the microorganisms, we achieve high resolution (~1 µm) imaging and long term culture of motile microorganisms over ultra large field-of-view (5.7 mm × 4.4 mm) in a specialized ePetri platform. We apply the pixel super-resolution reconstruction to a set of low-resolution shadow images of the microorganisms as they move across the sensing area of an image sensor chip and render an improved resolution image. We perform longitudinal study of Euglena gracilis cultured in an ePetri platform and image based analysis on the motion and morphology of the cells. The ePetri device for imaging non-motile cells are also demonstrated, by using the sweeping illumination of a light emitting diode (LED) matrix for pixel super-resolution reconstruction of sub-pixel shifted shadow images. Using this prototype device, we demonstrate the detection of waterborne parasites for the effective diagnosis of enteric parasite infection in resource-limited settings.

Then, we demonstrate the adaptation of a smartphone’s camera to function as a compact lensless microscope, which uses ambient illumination as its light source and does not require the incorporation of a dedicated light source. The method is also based on the image reconstruction with sweeping illumination technique, where the sequence of images are captured while the user is manually tilting the device around any ambient light source, such as the sun or a lamp. Image acquisition and reconstruction is performed on the device using a custom-built android application, constructing a stand-alone imaging device for field applications. We discuss the construction of the device using a commercial smartphone and demonstrate the imaging capabilities of our system.

Finally, we report on the implementation of fluorescence chip-scale microscope, based on a silo-filter structure fabricated on the pixel array of a CMOS image sensor. The extruded pixel design with metal walls between neighboring pixels successfully guides fluorescence emission through the thick absorptive filter to the photodiode layer of a pixel. Our silo-filter CMOS image sensor prototype achieves 13-µm resolution for fluorescence imaging over a wide field-of-view (4.8 mm × 4.4 mm). Here, we demonstrate bright-field and fluorescence longitudinal imaging of living cells in a compact, low-cost configuration.

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Wide field-of-view (FOV) microscopy is of high importance to biological research and clinical diagnosis where a high-throughput screening of samples is needed. This thesis presents the development of several novel wide FOV imaging technologies and demonstrates their capabilities in longitudinal imaging of living organisms, on the scale of viral plaques to live cells and tissues.

The ePetri Dish is a wide FOV on-chip bright-field microscope. Here we applied an ePetri platform for plaque analysis of murine norovirus 1 (MNV-1). The ePetri offers the ability to dynamically track plaques at the individual cell death event level over a wide FOV of 6 mm × 4 mm at 30 min intervals. A density-based clustering algorithm is used to analyze the spatial-temporal distribution of cell death events to identify plaques at their earliest stages. We also demonstrate the capabilities of the ePetri in viral titer count and dynamically monitoring plaque formation, growth, and the influence of antiviral drugs.

We developed another wide FOV imaging technique, the Talbot microscope, for the fluorescence imaging of live cells. The Talbot microscope takes advantage of the Talbot effect and can generate a focal spot array to scan the fluorescence samples directly on-chip. It has a resolution of 1.2 μm and a FOV of ~13 mm2. We further upgraded the Talbot microscope for the long-term time-lapse fluorescence imaging of live cell cultures, and analyzed the cells’ dynamic response to an anticancer drug.

We present two wide FOV endoscopes for tissue imaging, named the AnCam and the PanCam. The AnCam is based on the contact image sensor (CIS) technology, and can scan the whole anal canal within 10 seconds with a resolution of 89 μm, a maximum FOV of 100 mm × 120 mm, and a depth-of-field (DOF) of 0.65 mm. We also demonstrate the performance of the AnCam in whole anal canal imaging in both animal models and real patients. In addition to this, the PanCam is based on a smartphone platform integrated with a panoramic annular lens (PAL), and can capture a FOV of 18 mm × 120 mm in a single shot with a resolution of 100─140 μm. In this work we demonstrate the PanCam’s performance in imaging a stained tissue sample.