Pub Date : 2014-04-17DOI: 10.1109/SAS.2014.6798947
Arvind Rajan, Y. Kuang, M. Ooi, S. Demidenko
Polynomial regression model is very important in the modeling and characterization of sensors. The uncertainty propagation through the polynomial nonlinearity can only be estimated through numerical simulation or linearization approximation according to the Guide to the expression of Uncertainty in Measurement. This paper developed a general cookbook style guide to derive the analytical expression of uncertainty propagating through the polynomial regression models. The proposed method can be easily incorporated into any computer algebra system for reliable and fast evaluation. Specific expressions are derived explicitly for some of the most commonly used low order polynomial regression models. The framework is applied to a few recently published sensor and measurement system models.
{"title":"Standard Uncertainty estimation on polynomial regression models","authors":"Arvind Rajan, Y. Kuang, M. Ooi, S. Demidenko","doi":"10.1109/SAS.2014.6798947","DOIUrl":"https://doi.org/10.1109/SAS.2014.6798947","url":null,"abstract":"Polynomial regression model is very important in the modeling and characterization of sensors. The uncertainty propagation through the polynomial nonlinearity can only be estimated through numerical simulation or linearization approximation according to the Guide to the expression of Uncertainty in Measurement. This paper developed a general cookbook style guide to derive the analytical expression of uncertainty propagating through the polynomial regression models. The proposed method can be easily incorporated into any computer algebra system for reliable and fast evaluation. Specific expressions are derived explicitly for some of the most commonly used low order polynomial regression models. The framework is applied to a few recently published sensor and measurement system models.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114877292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-04-17DOI: 10.1109/SAS.2014.6798918
Jabal Raval, B. Jagyasi
In this paper, a Neural Network based data aggregation approach to detect the binary events in a multi-hop Wireless Sensor Network has been proposed. We envision every node in a network as a unit of neuron which gets trained by using the neural network based back propagation algorithm. As compared to the LMS based Adaptive Weighted Aggregation scheme for tree network, the proposed Neural Network based wireless sensor network approach leads to a significant improvement in detection accuracy without much energy losses due to communication and computation overhead. We also compare the detection accuracy of the proposed Neural Network based scheme with that of the non-adaptive Bayesian approach which requires apriori knowledge of the sensor's performance indices.
{"title":"Distributed detection in Neural Network based multihop Wireless Sensor Network","authors":"Jabal Raval, B. Jagyasi","doi":"10.1109/SAS.2014.6798918","DOIUrl":"https://doi.org/10.1109/SAS.2014.6798918","url":null,"abstract":"In this paper, a Neural Network based data aggregation approach to detect the binary events in a multi-hop Wireless Sensor Network has been proposed. We envision every node in a network as a unit of neuron which gets trained by using the neural network based back propagation algorithm. As compared to the LMS based Adaptive Weighted Aggregation scheme for tree network, the proposed Neural Network based wireless sensor network approach leads to a significant improvement in detection accuracy without much energy losses due to communication and computation overhead. We also compare the detection accuracy of the proposed Neural Network based scheme with that of the non-adaptive Bayesian approach which requires apriori knowledge of the sensor's performance indices.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128204671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-04-17DOI: 10.1109/SAS.2014.6798911
M. Hofbauer, J. Seiter, H. Zimmermann
A frequency-shifted feedback (FSF) laser in combination with an interferometer is a very accurate range sensing tool. In this paper, an FSF fiber laser with an output spectrum in the 777.5 nm range is presented. The cavity of the laser works in the 1555 nm range, enabling the use of cheap standard telecom products. Since a wavelength of 1555 nm is not detectable with silicon semiconductor devices, the output of the laser is frequency-doubled by a periodically poled lithium niobate (PPLN) crystal, which shifts the output spectrum from 1555 nm to 777.5 nm. It could be shown that frequency doubling is a feasible way to shift the output spectrum of the laser to a range which is detectable by silicon, without destroying the special properties of the FSF laser.
{"title":"Development of a frequency-shifted feedback fiber laser at 777.5 nm for range sensing applications","authors":"M. Hofbauer, J. Seiter, H. Zimmermann","doi":"10.1109/SAS.2014.6798911","DOIUrl":"https://doi.org/10.1109/SAS.2014.6798911","url":null,"abstract":"A frequency-shifted feedback (FSF) laser in combination with an interferometer is a very accurate range sensing tool. In this paper, an FSF fiber laser with an output spectrum in the 777.5 nm range is presented. The cavity of the laser works in the 1555 nm range, enabling the use of cheap standard telecom products. Since a wavelength of 1555 nm is not detectable with silicon semiconductor devices, the output of the laser is frequency-doubled by a periodically poled lithium niobate (PPLN) crystal, which shifts the output spectrum from 1555 nm to 777.5 nm. It could be shown that frequency doubling is a feasible way to shift the output spectrum of the laser to a range which is detectable by silicon, without destroying the special properties of the FSF laser.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121832381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-04-17DOI: 10.1109/SAS.2014.6798913
Minhhuy Le, Jungmin Kim, H. Do, Jinyi Lee
This study proposes a 2-D bobbin-type magnetic field vector camera in nondestructive testing for inspection of corrosions in inner and outer diameter (ID and OD) of a small-bore piping system. 16.1 mm diameter bobbin probe was produced by integrated of 71 Hall sensors (BIHaS) and 71 Giant magnetoresistance sensors (BIGiS) in two circumferential lines at interval of 0.6 mm. The BIHaS and BIGiS could measure radial and axial components of alternating magnetic field. Thus ID and OD corrosions could be imaged in a 2-D magnetic field vector. Two small-bore copper (16.56 mm inner diameter, 1.27 mm thickness) and titanium (17.28 mm inner diameter, 0.86 mm thickness) pipes with ID and OD corrosions were inspected and presented in this paper. The measured signal of each sensor array was displayed in a single contour plot and combined 2-D vector plot in real-time during scan.
{"title":"2-D vector field visualization of corrosion in a small-bore piping system using bobbin-type integrated Hall and GMR sensors arrays","authors":"Minhhuy Le, Jungmin Kim, H. Do, Jinyi Lee","doi":"10.1109/SAS.2014.6798913","DOIUrl":"https://doi.org/10.1109/SAS.2014.6798913","url":null,"abstract":"This study proposes a 2-D bobbin-type magnetic field vector camera in nondestructive testing for inspection of corrosions in inner and outer diameter (ID and OD) of a small-bore piping system. 16.1 mm diameter bobbin probe was produced by integrated of 71 Hall sensors (BIHaS) and 71 Giant magnetoresistance sensors (BIGiS) in two circumferential lines at interval of 0.6 mm. The BIHaS and BIGiS could measure radial and axial components of alternating magnetic field. Thus ID and OD corrosions could be imaged in a 2-D magnetic field vector. Two small-bore copper (16.56 mm inner diameter, 1.27 mm thickness) and titanium (17.28 mm inner diameter, 0.86 mm thickness) pipes with ID and OD corrosions were inspected and presented in this paper. The measured signal of each sensor array was displayed in a single contour plot and combined 2-D vector plot in real-time during scan.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127283285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-04-17DOI: 10.1109/SAS.2014.6798966
J. Bommer, A. Robb, R. Martinez, Shashi Ramamurthy, Jason Harrigan, H. Muniganti, Vivekanand Mannangi, K. Vinoy
A wireless fuel quantity indication system (FQIS) has been developed using an RFID-enabled sensing platform. The system comprises a fully passive tag, modified reader protocol, capacitive fuel probe, and auxiliary antenna for additional energy harvesting. Results of fluid testing show sensitivity to changes in fluid height of less than 0.25in. An RF-DC harvesting circuit was developed, which delivers up to 5dBm of input power through a remote radio frequency (RF) source. Testing was conducted in a loaded reverberation chamber to emulate the fuel tank environment. Results demonstrate feasibility of the remote source to power the sensor with less than 1W of maximum transmit power and under 100ms dwell time (100mW average power) into the tank. This indicates adequate coverage for large transport aircraft at safe operating levels with a sample rate of up to 1 sample/s.
{"title":"Wireless aircraft fuel quantity indication system","authors":"J. Bommer, A. Robb, R. Martinez, Shashi Ramamurthy, Jason Harrigan, H. Muniganti, Vivekanand Mannangi, K. Vinoy","doi":"10.1109/SAS.2014.6798966","DOIUrl":"https://doi.org/10.1109/SAS.2014.6798966","url":null,"abstract":"A wireless fuel quantity indication system (FQIS) has been developed using an RFID-enabled sensing platform. The system comprises a fully passive tag, modified reader protocol, capacitive fuel probe, and auxiliary antenna for additional energy harvesting. Results of fluid testing show sensitivity to changes in fluid height of less than 0.25in. An RF-DC harvesting circuit was developed, which delivers up to 5dBm of input power through a remote radio frequency (RF) source. Testing was conducted in a loaded reverberation chamber to emulate the fuel tank environment. Results demonstrate feasibility of the remote source to power the sensor with less than 1W of maximum transmit power and under 100ms dwell time (100mW average power) into the tank. This indicates adequate coverage for large transport aircraft at safe operating levels with a sample rate of up to 1 sample/s.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129049680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-04-17DOI: 10.1109/SAS.2014.6798956
M. Schaefer, D. Lamb, Ronald C. Bradbury
Active optical sensors that contain their own modulated light sources are becoming popular for “sensing” photosynthetically-active biomass in crops and pastures. These sensors detect optical reflectance to derive spectral vegetation indices, such as the normalised difference vegetation index (NDVI), and are subsequently calibrated to measure plant parameters e.g. biomass. However, research has demonstrated the accuracy of the derived measurements can often be improved by including both a spectral index and a corresponding measure of plant height. This paper describes an active, optical sensor that integrates modulated reflectance sensing with the ability to measure (range) the distance between the source and a target surface. Two ranging techniques are evaluated; one based on the inverse square law (ISL) of reflected radiation and another based on a position-sensitive detector (PSD). Both ranging methods proved capable of reliably delineating target distances out to 4.0 m from the source. Over this range, the PSD detector exhibited a distance-invariant RMSE of ± 2.6 cm whilst the ISL method exhibited an almost linear increase in error of ± 25 % of the measured distance to a spectralon target. Application to a vegetative target (Kikuyu grass), demonstrated the ISL ranging method to yield an average RMSE of ± 3.0 cm in the range of 0.60-1.40 m, while the average RMSE of the PSD over a range of 0.50-1.10 m was observed to be ± 10.0 cm. Despite superior accuracy, target reflectance variations may prove problematic in the use of a PSD ranging sensor and requires further investigation.
{"title":"A comparison of two ranging approaches in an active, optical plant canopy sensor","authors":"M. Schaefer, D. Lamb, Ronald C. Bradbury","doi":"10.1109/SAS.2014.6798956","DOIUrl":"https://doi.org/10.1109/SAS.2014.6798956","url":null,"abstract":"Active optical sensors that contain their own modulated light sources are becoming popular for “sensing” photosynthetically-active biomass in crops and pastures. These sensors detect optical reflectance to derive spectral vegetation indices, such as the normalised difference vegetation index (NDVI), and are subsequently calibrated to measure plant parameters e.g. biomass. However, research has demonstrated the accuracy of the derived measurements can often be improved by including both a spectral index and a corresponding measure of plant height. This paper describes an active, optical sensor that integrates modulated reflectance sensing with the ability to measure (range) the distance between the source and a target surface. Two ranging techniques are evaluated; one based on the inverse square law (ISL) of reflected radiation and another based on a position-sensitive detector (PSD). Both ranging methods proved capable of reliably delineating target distances out to 4.0 m from the source. Over this range, the PSD detector exhibited a distance-invariant RMSE of ± 2.6 cm whilst the ISL method exhibited an almost linear increase in error of ± 25 % of the measured distance to a spectralon target. Application to a vegetative target (Kikuyu grass), demonstrated the ISL ranging method to yield an average RMSE of ± 3.0 cm in the range of 0.60-1.40 m, while the average RMSE of the PSD over a range of 0.50-1.10 m was observed to be ± 10.0 cm. Despite superior accuracy, target reflectance variations may prove problematic in the use of a PSD ranging sensor and requires further investigation.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132515232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-04-17DOI: 10.1109/SAS.2014.6798914
Jungmin Kim, Minhhuy Le, Jinyi Lee
Nondestructive testing and evaluation of aircraft are a great importance from the viewpoint of the integrity and flight safety. In aircraft structures, damage is likely to be observed around the rivets that connect the skin to the frames. This paper presents a sensor system which includes a linearly integrated solid-state Hall sensor array (LIHaS). The LIHaS has 64 InSb Hall sensors arrayed in 0.52 mm of interval respect to 33.28 mm length of measurement. The sensor system was tested on two flat layers of Aluminium alloy for inspecting far-side corrosions having 6~14 mm of diameter and 0.1~1.27 mm of depth.
{"title":"Non-destructive evaluation of far-side corrosion around the multi-layered rivet by using the solid-state hall sensor array","authors":"Jungmin Kim, Minhhuy Le, Jinyi Lee","doi":"10.1109/SAS.2014.6798914","DOIUrl":"https://doi.org/10.1109/SAS.2014.6798914","url":null,"abstract":"Nondestructive testing and evaluation of aircraft are a great importance from the viewpoint of the integrity and flight safety. In aircraft structures, damage is likely to be observed around the rivets that connect the skin to the frames. This paper presents a sensor system which includes a linearly integrated solid-state Hall sensor array (LIHaS). The LIHaS has 64 InSb Hall sensors arrayed in 0.52 mm of interval respect to 33.28 mm length of measurement. The sensor system was tested on two flat layers of Aluminium alloy for inspecting far-side corrosions having 6~14 mm of diameter and 0.1~1.27 mm of depth.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131404954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-04-17DOI: 10.1109/SAS.2014.6798924
Eunjeh Hyun, Seungwoo Noh, Chiyul Yoon, Hee Chan Kim
The ElectroMechanical Film (EMFi), a thin and flexible piezoelectric material, has been widely used as a mechanical sensor or actuator. Especially in Biomedical Engineering field, many researchers have used EMFi for measuring ballistocardiogram (BCG) which is a mechanical signal caused by blood ejection from heart. However, previous methods required special equipments installed on a chair or a bed to measure BCG. In this preliminary study, we designed a flexible patch type sensor that can measure electrical and mechanical signal simultaneously on a single unit. The Ballistocardiogram-Electrocardiogram patch (BEpatch), integrated with flexible circuit and attached to chest, can successfully measure fine electrocardiogram (ECG) and BCG signals simultaneously. The result shows that BEpatch can be used for continuous monitoring of bio-signals in a simple and comfortable manner, thereby, advantageous as a wearable health care device.
{"title":"Patch type integrated sensor system for measuring electrical and mechanical cardiac activities","authors":"Eunjeh Hyun, Seungwoo Noh, Chiyul Yoon, Hee Chan Kim","doi":"10.1109/SAS.2014.6798924","DOIUrl":"https://doi.org/10.1109/SAS.2014.6798924","url":null,"abstract":"The ElectroMechanical Film (EMFi), a thin and flexible piezoelectric material, has been widely used as a mechanical sensor or actuator. Especially in Biomedical Engineering field, many researchers have used EMFi for measuring ballistocardiogram (BCG) which is a mechanical signal caused by blood ejection from heart. However, previous methods required special equipments installed on a chair or a bed to measure BCG. In this preliminary study, we designed a flexible patch type sensor that can measure electrical and mechanical signal simultaneously on a single unit. The Ballistocardiogram-Electrocardiogram patch (BEpatch), integrated with flexible circuit and attached to chest, can successfully measure fine electrocardiogram (ECG) and BCG signals simultaneously. The result shows that BEpatch can be used for continuous monitoring of bio-signals in a simple and comfortable manner, thereby, advantageous as a wearable health care device.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123151868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-04-17DOI: 10.1109/SAS.2014.6798970
Justin Cappos, Lai Wang, Richard S. Weiss, Yi Yang, Yanyan Zhuang
For many people, smartphones serve as a technical interface to the modern world. These smart devices have embedded on-board sensors, such as accelerometers, gyroscopes, GPS sensors, and cameras, which can be used to develop new mobile applications. However, the sensors also pose privacy risks to users. This work describes BlurSense, a tool that provides secure and customizable access to all of the sensors on smartphones, tablets, and similar end user devices. The current access control to the smartphone resources, such as sensor data, is static and coarse-grained. BlurSense is a dynamic, fine-grained, flexible access control mechanism, acting as a line of defense that allows users to define and add privacy filters. As a result, the user can expose filtered sensor data to untrusted apps, and researchers can collect data in a way that safeguards users' privacy.
{"title":"BlurSense: Dynamic fine-grained access control for smartphone privacy","authors":"Justin Cappos, Lai Wang, Richard S. Weiss, Yi Yang, Yanyan Zhuang","doi":"10.1109/SAS.2014.6798970","DOIUrl":"https://doi.org/10.1109/SAS.2014.6798970","url":null,"abstract":"For many people, smartphones serve as a technical interface to the modern world. These smart devices have embedded on-board sensors, such as accelerometers, gyroscopes, GPS sensors, and cameras, which can be used to develop new mobile applications. However, the sensors also pose privacy risks to users. This work describes BlurSense, a tool that provides secure and customizable access to all of the sensors on smartphones, tablets, and similar end user devices. The current access control to the smartphone resources, such as sensor data, is static and coarse-grained. BlurSense is a dynamic, fine-grained, flexible access control mechanism, acting as a line of defense that allows users to define and add privacy filters. As a result, the user can expose filtered sensor data to untrusted apps, and researchers can collect data in a way that safeguards users' privacy.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124314221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-04-17DOI: 10.1109/SAS.2014.6798945
S. Abeysekera, M. Ooi, Y. Kuang, Chee Pin Tan, S. Hassan
Pathologists spend nearly 80% of their time analysing pathological tissue samples. In addition, the diagnosis is subject to inter/intra-observer variability. Thus to increase productivity and repeatability, a new field known as Computational Pathology has emerged which combines the field of pathology with computer vision, pattern recognition and machine learning. This research develops a new computational pathology framework specifically to aid with detecting a condition known as spongiosis caused by Newcastle Disease Virus infection in poultry. It combines the use of multispectral imaging with feature extraction and classification to detect areas of spongiosis in tissue of infected poultry. The success of this framework is the first step towards a completely automated diagnosis tool for histopathology.
{"title":"Detecting spongiosis in stained histopathological specimen using multispectral imaging and machine learning","authors":"S. Abeysekera, M. Ooi, Y. Kuang, Chee Pin Tan, S. Hassan","doi":"10.1109/SAS.2014.6798945","DOIUrl":"https://doi.org/10.1109/SAS.2014.6798945","url":null,"abstract":"Pathologists spend nearly 80% of their time analysing pathological tissue samples. In addition, the diagnosis is subject to inter/intra-observer variability. Thus to increase productivity and repeatability, a new field known as Computational Pathology has emerged which combines the field of pathology with computer vision, pattern recognition and machine learning. This research develops a new computational pathology framework specifically to aid with detecting a condition known as spongiosis caused by Newcastle Disease Virus infection in poultry. It combines the use of multispectral imaging with feature extraction and classification to detect areas of spongiosis in tissue of infected poultry. The success of this framework is the first step towards a completely automated diagnosis tool for histopathology.","PeriodicalId":125872,"journal":{"name":"2014 IEEE Sensors Applications Symposium (SAS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129195958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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