|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | A deep learning-enabled portable imaging flow cytometer for cost-effective, highthroughput, and label-free analysis of natural water samples显示文摘We report a deep learning-enabled field-portable and cost-effective imaging flow cytometer that automatically captures phase-contrast color images of the contents of a continuously flowing water sample at a throughput of 100 mL/h.The device is based on partially coherent lens-free holographic microscopy and acquires the diffraction patterns of flowing micro-objects inside a microfluidic channel.These holographic diffraction patterns are reconstructed in real time using a deep learning-based phase-recovery and image-reconstruction method to produce a color image of each micro-object without the use of external labeling.Motion blur is eliminated by simultaneously illuminating the sample with red,green,and blue light-emitting diodes that are pulsed.Operated by a laptop computer,this portable device measures 15.5 cm×15 cm×12.5 cm,weighs 1 kg,and compared to standard imaging flow cytometers,it provides extreme reductions of cost,size and weight while also providing a high volumetric throughput over a large object size range.We demonstrated the capabilities of this device by measuring ocean samples at the Los Angeles coastline and obtaining images of its micro-and nanoplankton composition.Furthermore,we measured the concentration of a potentially toxic alga(Pseudo-nitzschia)in six public beaches in Los Angeles and achieved good agreement with measurements conducted by the California Department of Public Health.The cost-effectiveness,compactness,and simplicity of this computational platform might lead to the creation of a network of imaging flow cytometers for largescale and continuous monitoring of the ocean microbiome,including its plankton composition. | Zoltán Gӧrӧcs Miu Tamamitsu Vittorio Bianco Patrick Wolf Shounak Roy Koyoshi Shindo Kyrollos Yanny Yichen Wu Hatice Ceylan Koydemir Yair Rivenson Aydogan Ozcan | 2018 | Light(Science & Applications)2018，7，1： | 14 |
| 2 | Phase recovery and holographic image reconstruction using deep learning in neural networks显示文摘Phase recovery from intensity-only measurements forms the heart of coherent imaging techniques and holography.In this study,we demonstrate that a neural network can learn to perform phase recovery and holographic image reconstruction after appropriate training.This deep learning-based approach provides an entirely new framework to conduct holographic imaging by rapidly eliminating twin-image and self-interference-related spatial artifacts.This neural network-based method is fast to compute and reconstructs phase and amplitude images of the objects using only one hologram,requiring fewer measurements in addition to being computationally faster.We validated this method by reconstructing the phase and amplitude images of various samples,including blood and Pap smears and tissue sections.These results highlight that challenging problems in imaging science can be overcome through machine learning,providing new avenues to design powerful computational imaging systems. | Yair Rivenson Yibo Zhang Harun Günaydın Da Teng Aydogan Ozcan | 2017 | Light(Science & Applications)2017，6，1： | 5 |
| 3 | Air quality monitoring using mobile microscopy and machine learning显示文摘Rapid,accurate and high-throughput sizing and quantification of particulate matter(PM)in air is crucial for monitoring and improving air quality.In fact,particles in air with a diameter of≤2.5μm have been classified as carcinogenic by the World Health Organization.Here we present a field-portable cost-effective platform for high-throughput quantification of particulate matter using computational lens-free microscopy and machine-learning.This platform,termed c-Air,is also integrated with a smartphone application for device control and display of results.This mobile device rapidly screens 6.5 L of air in 30 s and generates microscopic images of the aerosols in air.It provides statistics of the particle size and density distribution with a sizing accuracy of~93%.We tested this mobile platform by measuring the air quality at different indoor and outdoor environments and measurement times,and compared our results to those of an Environmental Protection Agency–approved device based on beta-attenuation monitoring,which showed strong correlation to c-Air measurements.Furthermore,we used c-Air to map the air quality around Los Angeles International Airport(LAX)over 24 h to confirm that the impact of LAX on increased PM concentration was present even at 47 km away from the airport,especially along the direction of landing flights.With its machinelearning-based computational microscopy interface,c-Air can be adaptively tailored to detect specific particles in air,for example,various types of pollen and mold and provide a cost-effective mobile solution for highly accurate and distributed sensing of air quality. | Yi-Chen Wu Ashutosh Shiledar Yi-Cheng Li Jeffrey Wong Steve Feng Xuan Chen Christine Chen Kevin Jin Saba Janamian Zhe Yang Zachary Scott Ballard Zoltán Göröcs Alborz Feizi Aydogan Ozcan | 2017 | Light(Science & Applications)2017，6，1： | 5 |
| 4 | Modified pudendal thigh flap for perineoscrotal reconstruction: a case of Leriche syndrome with rapidly progressing Fournier's gangrene显示文摘 | Coruh A Akcali Y Ozcan N | 2004 | Urology2004，64，5： | 1 |
| 5 | Dexmedetomidine reduces the ischemia-reperfusion injury markers during upper extremity surgery with tourniquet显示文摘 | Yagmurdur H Ozcan N Dokumaci F | 2008 | J Hand Surg Am2008，33，6： | 1 |
| 6 | Structural Controls on Carlin - Type Gold Mineralization in the Gold Bar District, Eureka Coun- ty, Nevada显示文摘 | Ozcan Y Eric P N Murray W H | 2003 | Economic Geology2003，，98： | 1 |
| 7 | Clarithromycin in the treatment of RSV bronchiolitis : a double-blind, randomised, placebo-controlled trial显示文摘 | Tahan F Ozcan A Koc N | 2007 | Eur Respir J2007，29，： | 1 |
| 8 | Efficacy of lornoxicam in postoperative analgesia after total knee replacement surgery 显示文摘 | Inan N Ozcan N Takmaz SA | 2007 | Agri2007，19，2： | 1 |
| 9 | Thermodynamic assessment of gas removal systems for single-flash geothermal power plants显示文摘 | Ozcan N Y Gokcen G | 2009 | Ap- plied Thermal Engineering2009，29，1415： | 1 |
| 10 | A comparison of four intravenous sedation techniques and bispectral index monitorin in sinonasalsurgery显示文摘 | Buyukkocak N Ozcan S Daphan C | 2003 | Anesth Int Care2003，31，2： | 1 |
| 11 | A comparison of four intravenous sedation techniques and bispectral index monitoring in sinonasalsurgery显示文摘 | Buyukkocak N Ozcan S Daphan C | 2003 | Anesth Int Care2003，31，2： | 1 |
| 12 | Comparison of the effects of fentanyl,remifentanil,and dexmedetomidine on neuromuscular blockade显示文摘 | Ozcan A Ozcan N Gulec H | 2012 | J Anesth2012，26，2： | 1 |
| 13 | Percutaneous transhepatic removal of bile duct stones: results of 261 patients显示文摘 | Ozcan N Kahriman G Mavili E | 2012 | Cardiovasc Intervent Radiol2012，35，4： | 1 |
| 14 | Increased frequency of ultrasonographic findings suggestive of renal stones in patients with ankylosing spondylitis 显示文摘 | KORKMAZ C OZCAN A AKCAR N | 2005 | Clin Exp Rheumatol2005，23，3： | 1 |
| 15 | Dexmedetomidine reduces the ischemia-reperfusion injury markers during upper extremity surgery with tourniquet显示文摘 | Yagmurdur H Ozcan N | 2008 | Hand Surg Am2008，33，6： | 1 |
| 16 | Antifungal pmpertles of Bome herb decoction显示文摘 | Ozcan M Boyraz N | 2000 | Europe Food Research and Technology2000，212，1： | 1 |
| 17 | Global robust stability analysis of neural networks with multiple time delays 显示文摘 | Ozcan N Arik S | 2006 | IEEE Trans on Circuits Systems2006，35，1： | 1 |
| 18 | Double layered autogenous vein graft patch reconstruction of the common carotid-internal jugular fistula caused by gunshot wound显示文摘 | Kaklikkaya I Ozcan F Kutlu N | 1999 | J Cardiovasc Surg (Tori no)1999，40，3： | 1 |
| 19 | The use of expressive methods for developing empathic skills显示文摘 | Ozcan NK Bilgin H Eracar N | | 0，，02： | 1 |
| 20 | Structural and spectroscopic characteristics of two new dibenzylbutane type lignans from Taxus baccata L, 显示文摘 | Erdemoglu N Sener B Ozcan Y | 2003 | J Mol Struct2003，655，3： | 1 |
您所在的机构暂未开通此部分的功能，请联系管理员