Toward the development of miniaturized imaging systems for detection of pre-cancer

Descour, Michael R.; Kärkkäinen, Anu; Rogers, Jeremy D.; Liang, Chunjun; Weinstein, R. S.; Rantala, Juha; Kilic, Bahattin; Madenci, Erdogan; Richards‐Kortum, Rebecca; Anslyn, Eric V.; Dupuis, R. D.; Schul, R.J.; Willison, C. G.; Tigges, C.P.

doi:10.1109/3.980264

Cited by 35 publications

(15 citation statements)

References 14 publications

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“…Analysis of the basic diagnostic algorithms, implementation of quantification procedures such as quantitative immunohistochemistry, and videoconferencing systems for continuous education and case discussions have to be mentioned here [8,16]. Within the last few years, machines are commercially available that require about 5 minutes to digitize a whole slide [9,23]. They are equipped with magazines for about 300 slides, and delegate the digitized, so -called virtual slides for further processes such as human diagnostics or automated measurements within eight to 10 hours (night duty].…”

Section: Introductionmentioning

confidence: 99%

AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis.

Kayser

Görtler²,

Bogovac³

et al. 2010

Folia Histochem Cytobiol.

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Abstract:The technological progress in digitalization of complete histological glass slides has opened a new door in tissue -based diagnosis. The presentation of microscopic images as a whole in a digital matrix is called virtual slide. A virtual slide allows calculation and related presentation of image information that otherwise can only be seen by individual human performance. The digital world permits attachments of several (if not all) fields of view and the contemporary visualization on a screen. The presentation of all microscopic magnifications is possible if the basic pixel resolution is less than 0.25 microns. To introduce digital tissue -based diagnosis into the daily routine work of a surgical pathologist requires a new setup of workflow arrangement and procedures. The quality of digitized images is sufficient for diagnostic purposes; however, the time needed for viewing virtual slides exceeds that of viewing original glass slides by far. The reason lies in a slower and more difficult sampling procedure, which is the selection of information containing fields of view. By application of artificial intelligence, tissue -based diagnosis in routine work can be managed automatically in steps as follows: 1. The individual image quality has to be measured, and corrected, if necessary. 2. A diagnostic algorithm has to be applied. An algorithm has be developed, that includes both object based (object features, structures) and pixel based (texture) measures. 3. These measures serve for diagnosis classification and feedback to order additional information, for example in virtual immunohistochemical slides. 4. The measures can serve for automated image classification and detection of relevant image information by themselves without any labeling. 5. The pathologists' duty will not be released by such a system; to the contrary, it will manage and supervise the system, i.e., just working at a "higher level". Virtual slides are already in use for teaching and continuous education in anatomy and pathology. First attempts to introduce them into routine work have been reported. Application of AI has been established by automated immunohistochemical measurement systems (EAMUS, www.diagnomX.eu). The performance of automated diagnosis has been reported for a broad variety of organs at sensitivity and specificity levels >85%). The implementation of a complete connected AI supported system is in its childhood. Application of AI in digital tissue -based diagnosis will allow the pathologists to work as supervisors and no longer as primary "water carriers". Its accurate use will give them the time needed to concentrating on difficult cases for the benefit of their patients.

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Section: Introductionmentioning

confidence: 99%

AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis.

Kayser

Görtler²,

Bogovac³

et al. 2010

Folia Histochem Cytobiol.

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“…Naylor and Smith investigated ghost image formation using ray tracing [9,10]. Descour et al pointed out that ghost images and reflections severely limit the performance of some miniature microscopes [1]. A novel solution to some problematic ghost images was implemented using tilted lens elements with polynomial surfaces by Rogers et al [2].…”

Section: Introductionmentioning

confidence: 98%

“…In imaging applications, ghost images may cause contrast reduction, and may veil parts of the image of the nominal scene [1][2][3][4]. In high-power lasers, focused ghosts may damage the optical components if their irradiance exceeds the threshold nominal irradiance [5,6].…”

Section: Introductionmentioning

confidence: 99%

Optical performance of coherent and incoherent imaging systems in the presence of ghost images

et al. 2012

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Ghost image analysis is of interest for optical designers as ghost images may degrade image quality in imaging systems. In a previous paper by Abd El-Maksoud and Sasian [Appl. Opt. 50, 2305 (2011)10.1364/AO.50.002305], ghost image analysis for incoherent systems was evaluated using geometrical optics. Some criteria were presented to identify focused ghost images at the nominal image plane. The main goal of this paper is to provide a conceptual understanding of ghost image formation and its impact on the performance of imaging systems using wave theory and Fourier optics. To achieve this goal, a methodology is developed to model ghost images after considering diffraction effects. Expressions for the ghost diffraction point spread function and the ghost transfer function are presented. These functions are used to construct effective point spread and effective transfer functions. To provide insights on the developed theory, some simulation examples are provided and discussed.

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“…Indeed, optical components (lenses, mirrors, fiber holders, detectors, beam splitters) are microfabricated using "simple", well known and reliable processes [2], [3]. These components are then assembled together permitting the fabrication of complex 3D microstructures [4], [5], [6], [7]. The understanding of the microworld phenomena [8] and the automation of the micro-assembly tasks are currently under investigation.…”

Section: Introductionmentioning

confidence: 99%

A micro-assembly station used for 3D reconfigurable hybrid MOEMS assembly

Rabenorosoa

Clevy

Lutz

et al. 2009

2009 IEEE International Symposium on Assembly and Manufacturing

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Micro-assembly has been identified to be a critical technology in the microsystems technology and nanotechnology. The increasing needs of MOEMS (Micro-Opto-ElectroMechanical Systems) for the microsystems conducts to development of new concepts and skilled micro-assembly stations. This paper presents a 3D micro-assembly station used for the reconfigurable free space micro-optical benches (RFS-MOB) which are a promising type of MOEMS. The designed parts of RFS-MOB are assembled by using the developped microassembly station. Experimental results are shown and validate the effectiveness of the micro-assembly station and the microassembly strategies.

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Toward the development of miniaturized imaging systems for detection of pre-cancer

Cited by 35 publications

References 14 publications

AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis.

AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis.

Optical performance of coherent and incoherent imaging systems in the presence of ghost images

A micro-assembly station used for 3D reconfigurable hybrid MOEMS assembly

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