Performance Analysis of Three Microscope Slide Scanning Techniques
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Abstract:
The demands for digital pathology systems have increased dramatically in the last decade as Virtual Microscopy (VM) has gained increasing popularity. Many digital slide acquisition systems have been developed to meet this demand, utilising a variety of image scan techniques. However, the requirements for, and performance of, these scan techniques are largely undocumented. Therefore, in this paper we evaluate the three primary approaches to digital slide scanning in light field microscopy: field-of-view (FOV) scan, line scan and slanted specimen scan. Initially, we develop equations for each technique that estimates their theoretical scan times in terms data throughput rates. Next, we compare each system's performance based on the relationships between illumination, camera frame rates, data transfer rates and microscope stage speed. We conclude that slanted scan system capable of acquiring multiple focal planes in one pass have the potential to obtain the shortest scan times within current constraints on stage and camera hardware.Keywords:
Frame rate
Scan line
Depth of field
Autofocus
Field of view
Autofocus
Depth of field
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Autofocus
Depth of field
Field of view
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The speed of line scan imaging system is limited either by scanning technique or the frame rate of CCD and CMOS cameras. By using hybrid dispersion laser scanning technique, we built an ultra-fast line scan microscopic imaging system with record frame rate of 1GHz. This technique is promising to be used for capturing fast process, especially non-repetitive transient phenomena.
Frame rate
Scan line
Line (geometry)
Transient (computer programming)
Laser Scanning
Horizontal scan rate
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We introduce a solid state high throughput screening (ssHTS) imaging modality that uses a novel Newtonian telescope design to image multiple spatially separated samples without moving parts or robotics. Conventional high-throughput imaging modalities either require movement of the sample to the focal plane of the imaging system 1–3 or movement of the imaging system itself 4,5 , or use a wide-field approach to capture several samples in one frame. Schemes which move the sample or the imaging system can be mechanically complex and are inherently slow, while wide-field imaging systems have poor light collection efficiency and resolution compared to systems that image a single sample at a given time point. Our proposed ssHTS system uses a large parabolic reflector and an imaging lenses positioned at their focal distances above each sample. A fast LED array sequentially illuminate samples to generate images that are captured with a single camera placed at the focal point of the reflector. This optical configuration allows each sample to completely fill a sensors field of view. Since each LED illuminates a single sample and LED switch times are very fast, images from spatially separated samples can be captured at rates limited only by the camera’s frame rate. The system is demonstrated by imaging cardiac monolayer and Caenorhabditis elegans ( C. elegans ) preparations.
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Sample (material)
Field of view
Depth of field
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Auto-focusing is essential for the detection of minute defects in inspection equipments. We propose an optical system that can autofocus on a glass substrate and an algorithm that can adjust the focus quickly and accurately. The optical system uses Koehler illumination to measure the contrast of the field of view aperture, which is effective for plain glass. The auto-focusing algorithm using random forest is learned by setting the target value for the input image with the estimated focal length. When a new image is given, the focal length estimate is calculated. Various experiments have been performed on focus measurement using images acquired from various locations and show better results than others.
Autofocus
Depth of field
Aperture (computer memory)
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An autofocus circuit, based on measurement of the high spatial frequency image components, was designed for automated microscopic scanning of biological specimens. By careful consideration of the system transfer function, elimination of video end-of-line filter artifacts, correction for illumination instability, and incorporation of autogain, the focus measurement circuit attained the sensitivity and dynamic range necessary for robust operation even at the extremes of biological specimen detail encountered in exhaustive raster scans of thousands of fields. This new circuit exhibited a 25-fold improvement in dynamic range over a previous analog implementation, matched real-time digital performance at an order of magnitude lower cost, resulted in autofocus precision of 56 nm (or 10-fold better than the depth of field of the objective) in scanning experiments comprising over 10 000 microscope fields, and tracked focus at scanning speeds of up to 3.45 fields/s. Focus was correctly maintained in these scanning experiments without additional compensation for low-detail images. This circuit makes possible the widespread inclusion of high-performance autofocus as a low cost option in video microscopy systems.
Autofocus
Depth of field
Raster scan
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We report a method of high-speed phase contrast and bright field microscopy which permits large cell culture vessels to be scanned at much higher speed (up to 30 times faster) than when conventional methods are used without compromising image quality. The object under investigation moves continuously and is captured using a flash illumination which creates an exposure time short enough to prevent motion blur. During the scan the object always stays in focus due to a novel hardware-autofocus system.
Autofocus
Depth of field
Motion blur
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Wearable Video See-Through (VST) devices for Augmented Reality (AR) and for obtaining a Magnified View are taking hold in the medical and surgical fields. However, these devices are not yet usable in daily clinical practice, due to focusing problems and a limited depth of field. This study investigates the use of liquid-lens optics to create an autofocus system for wearable VST visors. The autofocus system is based on a Time of Flight (TOF) distance sensor and an active autofocus control system. The integrated autofocus system in the wearable VST viewers showed good potential in terms of providing rapid focus at various distances and a magnified view.
Autofocus
USable
Depth of field
Optical head-mounted display
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In this paper, we propose a technique for multiregion autofocusing. The objective is to make the objects of interest at the different distance locations well focused while maintaining the shallow depth of field. Based on the image sharpness analysis of interested regions, we determine the camera's best lens position and largest aperture size such that the depth of field encompasses all objects selected by the user. Thus, in addition to emphasize the objects of interest in photography, our method can also reduce the exposure for image stabilization. Experiments with real scene images are presented.
Autofocus
Depth of field
Computational photography
Camera lens
Aperture (computer memory)
Field of view
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The presented vision system integrates a focus tunable lens allows to perform fast autofocus and distance measurement at the same time. By deriving the best focus from the maximum position of a fitted distribution, it is not required to capture the image with the actual best focus during the autofocus sweep, resulting in high speed and robustness of the algorithm. In this work, we demonstrate that a focus tunable lens in conjunction with an autofocus algorithm can reliably measure distance to an arbitrary object in less than a second (depth from focus). The accuracy of the distance measurement is in line with the depth of field of the imaging system. No additional hardware is required apart from the imaging system comprising camera, objective lens and focus tunable lens. The fast and accurate focus and distance measurement enables and simplifies various applications ranging from robot vision to smart manufacturing control. The optics can be tailored to reach the desired precision and focus range, whereas there is generally a trade-off between the two.
Autofocus
Depth of field
Ranging
Robustness
Machine Vision
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