The Experts below are selected from a list of 4791 Experts worldwide ranked by ideXlab platform
Metin N Gurcan - One of the best experts on this subject based on the ideXlab platform.
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digital Otoscopy videos versus composite images a reader study to compare the accuracy of ent physicians
Laryngoscope, 2020Co-Authors: Hamidullah Binol, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Jay Shah, Jameson K Mattingly, Michael S Harris, Muhammad Khalid Khan Niazi, Theodoros Teknos, Metin N GurcanAbstract:Objectives/hypothesis With the increasing emphasis on developing effective telemedicine approaches in Otolaryngology, this study explored whether a single composite image stitched from a digital Otoscopy video provides acceptable diagnostic information to make an accurate diagnosis, as compared with that provided by the full video. Study design Diagnostic survey analysis. Methods Five Ear, Nose, and Throat (ENT) physicians reviewed the same set of 78 digital otoscope eardrum videos from four eardrum conditions: normal, effusion, retraction, and tympanosclerosis, along with the composite images generated by a SelectStitch method that selectively uses video frames with computer-assisted selection, as well as a Stitch method that incorporates all the video frames. Participants provided a diagnosis for each item along with a rating of diagnostic confidence. Diagnostic accuracy for each pathology of SelectStitch was compared with accuracy when reviewing the entire video clip and when reviewing the Stitch image. Results There were no significant differences in diagnostic accuracy for physicians reviewing SelectStitch images and full video clips, but both provided better diagnostic accuracy than Stitch images. The inter-reader agreement was moderate. Conclusions Equal to using full video clips, composite images of eardrums generated by SelectStitch provided sufficient information for ENTs to make the correct diagnoses for most pathologies. These findings suggest that use of a composite eardrum image may be sufficient for telemedicine approaches to ear diagnosis, eliminating the need for storage and transmission of large video files, along with future applications for improved documentation in electronic medical record systems, patient/family counseling, and clinical training. Level of evidence 3 Laryngoscope, 2020.
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digital Otoscopy videos versus composite images a reader study to compare the accuracy of ent physicians
medRxiv, 2020Co-Authors: Hamidullah Binol, Theodoros N Teknos, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Khalid Khan M Niazi, Jay Shah, Jameson K Mattingly, Michael S Harris, Metin N GurcanAbstract:Objectives: With the increasing emphasis on developing effective telemedicine approaches in Otolaryngology, this study explored whether a single composite image stitched from a digital Otoscopy video provides acceptable diagnostic information to make an accurate diagnosis, as compared with that provided by the full video. Methods: Five Ear, Nose, and Throat (ENT) physicians reviewed the same set of 78 digital otoscope eardrum videos from four eardrum conditions: normal, effusion, retraction, and tympanosclerosis, along with the composite images generated by a SelectStitch method that selectively uses video frames with computer-assisted selection, as well as a Stitch method that incorporates all the video frames. Participants provided a diagnosis for each item along with a rating of diagnostic confidence. Diagnostic accuracy for each pathology of SelectStitch was compared with accuracy when reviewing the entire video clip and when reviewing the Stitch image. Results: There were no significant differences in diagnostic accuracy for physicians reviewing SelectStitch images and full video clips, but both provided better diagnostic accuracy than Stitch images. The inter-reader agreement was moderate. Conclusion: Equal to using full video clips, composite images of eardrums generated by SelectStitch provided sufficient information for ENTs to make the correct diagnoses for most pathologies. These findings suggest that use of a composite eardrum image may be sufficient for telemedicine approaches to ear diagnosis, eliminating the need for storage and transmission of large video files, along with future applications for improved documentation in electronic medical record systems, patient/family counseling, and clinical training.
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autoscope automated Otoscopy image analysis to diagnose ear pathology and use of clinically motivated eardrum features
Proceedings of SPIE, 2017Co-Authors: Caglar Senaras, Aaron C Moberly, Theodoros N Teknos, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Metin N GurcanAbstract:In this study, we propose an automated Otoscopy image analysis system called Autoscope. To the best of our knowledge, Autoscope is the first system designed to detect a wide range of eardrum abnormalities by using high-resolution otoscope images and report the condition of the eardrum as “normal” or “abnormal.” In order to achieve this goal, first, we developed a preprocessing step to reduce camera-specific problems, detect the region of interest in the image, and prepare the image for further analysis. Subsequently, we designed a new set of clinically motivated eardrum features (CMEF). Furthermore, we evaluated the potential of the visual MPEG-7 descriptors for the task of tympanic membrane image classification. Then, we fused the information extracted from the CMEF and state-of-the-art computer vision features (CVF), which included MPEG-7 descriptors and two additional features together, using a state of the art classifier. In our experiments, 247 tympanic membrane images with 14 different types of abnormality were used, and Autoscope was able to classify the given tympanic membrane images as normal or abnormal with 84.6% accuracy.
Garth F Essig - One of the best experts on this subject based on the ideXlab platform.
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digital Otoscopy videos versus composite images a reader study to compare the accuracy of ent physicians
Laryngoscope, 2020Co-Authors: Hamidullah Binol, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Jay Shah, Jameson K Mattingly, Michael S Harris, Muhammad Khalid Khan Niazi, Theodoros Teknos, Metin N GurcanAbstract:Objectives/hypothesis With the increasing emphasis on developing effective telemedicine approaches in Otolaryngology, this study explored whether a single composite image stitched from a digital Otoscopy video provides acceptable diagnostic information to make an accurate diagnosis, as compared with that provided by the full video. Study design Diagnostic survey analysis. Methods Five Ear, Nose, and Throat (ENT) physicians reviewed the same set of 78 digital otoscope eardrum videos from four eardrum conditions: normal, effusion, retraction, and tympanosclerosis, along with the composite images generated by a SelectStitch method that selectively uses video frames with computer-assisted selection, as well as a Stitch method that incorporates all the video frames. Participants provided a diagnosis for each item along with a rating of diagnostic confidence. Diagnostic accuracy for each pathology of SelectStitch was compared with accuracy when reviewing the entire video clip and when reviewing the Stitch image. Results There were no significant differences in diagnostic accuracy for physicians reviewing SelectStitch images and full video clips, but both provided better diagnostic accuracy than Stitch images. The inter-reader agreement was moderate. Conclusions Equal to using full video clips, composite images of eardrums generated by SelectStitch provided sufficient information for ENTs to make the correct diagnoses for most pathologies. These findings suggest that use of a composite eardrum image may be sufficient for telemedicine approaches to ear diagnosis, eliminating the need for storage and transmission of large video files, along with future applications for improved documentation in electronic medical record systems, patient/family counseling, and clinical training. Level of evidence 3 Laryngoscope, 2020.
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digital Otoscopy videos versus composite images a reader study to compare the accuracy of ent physicians
medRxiv, 2020Co-Authors: Hamidullah Binol, Theodoros N Teknos, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Khalid Khan M Niazi, Jay Shah, Jameson K Mattingly, Michael S Harris, Metin N GurcanAbstract:Objectives: With the increasing emphasis on developing effective telemedicine approaches in Otolaryngology, this study explored whether a single composite image stitched from a digital Otoscopy video provides acceptable diagnostic information to make an accurate diagnosis, as compared with that provided by the full video. Methods: Five Ear, Nose, and Throat (ENT) physicians reviewed the same set of 78 digital otoscope eardrum videos from four eardrum conditions: normal, effusion, retraction, and tympanosclerosis, along with the composite images generated by a SelectStitch method that selectively uses video frames with computer-assisted selection, as well as a Stitch method that incorporates all the video frames. Participants provided a diagnosis for each item along with a rating of diagnostic confidence. Diagnostic accuracy for each pathology of SelectStitch was compared with accuracy when reviewing the entire video clip and when reviewing the Stitch image. Results: There were no significant differences in diagnostic accuracy for physicians reviewing SelectStitch images and full video clips, but both provided better diagnostic accuracy than Stitch images. The inter-reader agreement was moderate. Conclusion: Equal to using full video clips, composite images of eardrums generated by SelectStitch provided sufficient information for ENTs to make the correct diagnoses for most pathologies. These findings suggest that use of a composite eardrum image may be sufficient for telemedicine approaches to ear diagnosis, eliminating the need for storage and transmission of large video files, along with future applications for improved documentation in electronic medical record systems, patient/family counseling, and clinical training.
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diagnostic accuracy and confidence for Otoscopy are medical students receiving sufficient training
Laryngoscope, 2019Co-Authors: Weston L Niermeyer, Garth F Essig, Ramez Philips, Aaron C MoberlyAbstract:OBJECTIVES/HYPOTHESIS To assess the confidence and abilities of medical students to diagnose specific types of otologic pathology, and to determine how different training experiences in medical school impact these outcomes. STUDY DESIGN Survey analysis. METHODS Sixty third- and fourth-year medical students completed a computerized online survey. Participants answered questions about their otoscopic training experience and confidence, and provided diagnoses for 72 digital images taken with a high-definition video otoscope that showed common otologic pathologies of the tympanic membrane and middle ear space. RESULTS Most participants (65%) had received less exposure to otoscopic training in medical school than they expected. Confidence in diagnostic ability was low. For diagnostic ability, the mean percent correct across pathologies was 54% ± 7.7%. Medical school year (P = .006), intended specialty (P = .022), and total number of otolaryngology rotations (P = .048) were predictive of diagnostic accuracy on univariable logistic regression analyses, but medical school year (P = .039) was the only significant independent predictor in multivariable analysis. Intended specialty (P = .047) and total number of otolaryngology rotations (P = .035) were predictive of prequiz diagnostic confidence on univariable logistic regression analyses. CONCLUSIONS Medical students were not satisfied with their exposure to otoscopic training. Intended specialty, total number of otolaryngology rotations, and year in medical school predicted diagnostic accuracy. Intended specialty and total number of otolaryngology rotations predicted diagnostic confidence. Additional studies are needed to investigate how training experiences can be improved to optimize Otoscopy training during medical school. LEVEL OF EVIDENCE NA Laryngoscope, 129:1891-1897, 2019.
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autoscope automated Otoscopy image analysis to diagnose ear pathology and use of clinically motivated eardrum features
Proceedings of SPIE, 2017Co-Authors: Caglar Senaras, Aaron C Moberly, Theodoros N Teknos, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Metin N GurcanAbstract:In this study, we propose an automated Otoscopy image analysis system called Autoscope. To the best of our knowledge, Autoscope is the first system designed to detect a wide range of eardrum abnormalities by using high-resolution otoscope images and report the condition of the eardrum as “normal” or “abnormal.” In order to achieve this goal, first, we developed a preprocessing step to reduce camera-specific problems, detect the region of interest in the image, and prepare the image for further analysis. Subsequently, we designed a new set of clinically motivated eardrum features (CMEF). Furthermore, we evaluated the potential of the visual MPEG-7 descriptors for the task of tympanic membrane image classification. Then, we fused the information extracted from the CMEF and state-of-the-art computer vision features (CVF), which included MPEG-7 descriptors and two additional features together, using a state of the art classifier. In our experiments, 247 tympanic membrane images with 14 different types of abnormality were used, and Autoscope was able to classify the given tympanic membrane images as normal or abnormal with 84.6% accuracy.
Hamidullah Binol - One of the best experts on this subject based on the ideXlab platform.
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digital Otoscopy videos versus composite images a reader study to compare the accuracy of ent physicians
Laryngoscope, 2020Co-Authors: Hamidullah Binol, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Jay Shah, Jameson K Mattingly, Michael S Harris, Muhammad Khalid Khan Niazi, Theodoros Teknos, Metin N GurcanAbstract:Objectives/hypothesis With the increasing emphasis on developing effective telemedicine approaches in Otolaryngology, this study explored whether a single composite image stitched from a digital Otoscopy video provides acceptable diagnostic information to make an accurate diagnosis, as compared with that provided by the full video. Study design Diagnostic survey analysis. Methods Five Ear, Nose, and Throat (ENT) physicians reviewed the same set of 78 digital otoscope eardrum videos from four eardrum conditions: normal, effusion, retraction, and tympanosclerosis, along with the composite images generated by a SelectStitch method that selectively uses video frames with computer-assisted selection, as well as a Stitch method that incorporates all the video frames. Participants provided a diagnosis for each item along with a rating of diagnostic confidence. Diagnostic accuracy for each pathology of SelectStitch was compared with accuracy when reviewing the entire video clip and when reviewing the Stitch image. Results There were no significant differences in diagnostic accuracy for physicians reviewing SelectStitch images and full video clips, but both provided better diagnostic accuracy than Stitch images. The inter-reader agreement was moderate. Conclusions Equal to using full video clips, composite images of eardrums generated by SelectStitch provided sufficient information for ENTs to make the correct diagnoses for most pathologies. These findings suggest that use of a composite eardrum image may be sufficient for telemedicine approaches to ear diagnosis, eliminating the need for storage and transmission of large video files, along with future applications for improved documentation in electronic medical record systems, patient/family counseling, and clinical training. Level of evidence 3 Laryngoscope, 2020.
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digital Otoscopy videos versus composite images a reader study to compare the accuracy of ent physicians
medRxiv, 2020Co-Authors: Hamidullah Binol, Theodoros N Teknos, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Khalid Khan M Niazi, Jay Shah, Jameson K Mattingly, Michael S Harris, Metin N GurcanAbstract:Objectives: With the increasing emphasis on developing effective telemedicine approaches in Otolaryngology, this study explored whether a single composite image stitched from a digital Otoscopy video provides acceptable diagnostic information to make an accurate diagnosis, as compared with that provided by the full video. Methods: Five Ear, Nose, and Throat (ENT) physicians reviewed the same set of 78 digital otoscope eardrum videos from four eardrum conditions: normal, effusion, retraction, and tympanosclerosis, along with the composite images generated by a SelectStitch method that selectively uses video frames with computer-assisted selection, as well as a Stitch method that incorporates all the video frames. Participants provided a diagnosis for each item along with a rating of diagnostic confidence. Diagnostic accuracy for each pathology of SelectStitch was compared with accuracy when reviewing the entire video clip and when reviewing the Stitch image. Results: There were no significant differences in diagnostic accuracy for physicians reviewing SelectStitch images and full video clips, but both provided better diagnostic accuracy than Stitch images. The inter-reader agreement was moderate. Conclusion: Equal to using full video clips, composite images of eardrums generated by SelectStitch provided sufficient information for ENTs to make the correct diagnoses for most pathologies. These findings suggest that use of a composite eardrum image may be sufficient for telemedicine approaches to ear diagnosis, eliminating the need for storage and transmission of large video files, along with future applications for improved documentation in electronic medical record systems, patient/family counseling, and clinical training.
Charles A Elmaraghy - One of the best experts on this subject based on the ideXlab platform.
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digital Otoscopy videos versus composite images a reader study to compare the accuracy of ent physicians
Laryngoscope, 2020Co-Authors: Hamidullah Binol, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Jay Shah, Jameson K Mattingly, Michael S Harris, Muhammad Khalid Khan Niazi, Theodoros Teknos, Metin N GurcanAbstract:Objectives/hypothesis With the increasing emphasis on developing effective telemedicine approaches in Otolaryngology, this study explored whether a single composite image stitched from a digital Otoscopy video provides acceptable diagnostic information to make an accurate diagnosis, as compared with that provided by the full video. Study design Diagnostic survey analysis. Methods Five Ear, Nose, and Throat (ENT) physicians reviewed the same set of 78 digital otoscope eardrum videos from four eardrum conditions: normal, effusion, retraction, and tympanosclerosis, along with the composite images generated by a SelectStitch method that selectively uses video frames with computer-assisted selection, as well as a Stitch method that incorporates all the video frames. Participants provided a diagnosis for each item along with a rating of diagnostic confidence. Diagnostic accuracy for each pathology of SelectStitch was compared with accuracy when reviewing the entire video clip and when reviewing the Stitch image. Results There were no significant differences in diagnostic accuracy for physicians reviewing SelectStitch images and full video clips, but both provided better diagnostic accuracy than Stitch images. The inter-reader agreement was moderate. Conclusions Equal to using full video clips, composite images of eardrums generated by SelectStitch provided sufficient information for ENTs to make the correct diagnoses for most pathologies. These findings suggest that use of a composite eardrum image may be sufficient for telemedicine approaches to ear diagnosis, eliminating the need for storage and transmission of large video files, along with future applications for improved documentation in electronic medical record systems, patient/family counseling, and clinical training. Level of evidence 3 Laryngoscope, 2020.
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digital Otoscopy videos versus composite images a reader study to compare the accuracy of ent physicians
medRxiv, 2020Co-Authors: Hamidullah Binol, Theodoros N Teknos, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Khalid Khan M Niazi, Jay Shah, Jameson K Mattingly, Michael S Harris, Metin N GurcanAbstract:Objectives: With the increasing emphasis on developing effective telemedicine approaches in Otolaryngology, this study explored whether a single composite image stitched from a digital Otoscopy video provides acceptable diagnostic information to make an accurate diagnosis, as compared with that provided by the full video. Methods: Five Ear, Nose, and Throat (ENT) physicians reviewed the same set of 78 digital otoscope eardrum videos from four eardrum conditions: normal, effusion, retraction, and tympanosclerosis, along with the composite images generated by a SelectStitch method that selectively uses video frames with computer-assisted selection, as well as a Stitch method that incorporates all the video frames. Participants provided a diagnosis for each item along with a rating of diagnostic confidence. Diagnostic accuracy for each pathology of SelectStitch was compared with accuracy when reviewing the entire video clip and when reviewing the Stitch image. Results: There were no significant differences in diagnostic accuracy for physicians reviewing SelectStitch images and full video clips, but both provided better diagnostic accuracy than Stitch images. The inter-reader agreement was moderate. Conclusion: Equal to using full video clips, composite images of eardrums generated by SelectStitch provided sufficient information for ENTs to make the correct diagnoses for most pathologies. These findings suggest that use of a composite eardrum image may be sufficient for telemedicine approaches to ear diagnosis, eliminating the need for storage and transmission of large video files, along with future applications for improved documentation in electronic medical record systems, patient/family counseling, and clinical training.
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autoscope automated Otoscopy image analysis to diagnose ear pathology and use of clinically motivated eardrum features
Proceedings of SPIE, 2017Co-Authors: Caglar Senaras, Aaron C Moberly, Theodoros N Teknos, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Metin N GurcanAbstract:In this study, we propose an automated Otoscopy image analysis system called Autoscope. To the best of our knowledge, Autoscope is the first system designed to detect a wide range of eardrum abnormalities by using high-resolution otoscope images and report the condition of the eardrum as “normal” or “abnormal.” In order to achieve this goal, first, we developed a preprocessing step to reduce camera-specific problems, detect the region of interest in the image, and prepare the image for further analysis. Subsequently, we designed a new set of clinically motivated eardrum features (CMEF). Furthermore, we evaluated the potential of the visual MPEG-7 descriptors for the task of tympanic membrane image classification. Then, we fused the information extracted from the CMEF and state-of-the-art computer vision features (CVF), which included MPEG-7 descriptors and two additional features together, using a state of the art classifier. In our experiments, 247 tympanic membrane images with 14 different types of abnormality were used, and Autoscope was able to classify the given tympanic membrane images as normal or abnormal with 84.6% accuracy.
Nazhat Tajschaal - One of the best experts on this subject based on the ideXlab platform.
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digital Otoscopy videos versus composite images a reader study to compare the accuracy of ent physicians
Laryngoscope, 2020Co-Authors: Hamidullah Binol, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Jay Shah, Jameson K Mattingly, Michael S Harris, Muhammad Khalid Khan Niazi, Theodoros Teknos, Metin N GurcanAbstract:Objectives/hypothesis With the increasing emphasis on developing effective telemedicine approaches in Otolaryngology, this study explored whether a single composite image stitched from a digital Otoscopy video provides acceptable diagnostic information to make an accurate diagnosis, as compared with that provided by the full video. Study design Diagnostic survey analysis. Methods Five Ear, Nose, and Throat (ENT) physicians reviewed the same set of 78 digital otoscope eardrum videos from four eardrum conditions: normal, effusion, retraction, and tympanosclerosis, along with the composite images generated by a SelectStitch method that selectively uses video frames with computer-assisted selection, as well as a Stitch method that incorporates all the video frames. Participants provided a diagnosis for each item along with a rating of diagnostic confidence. Diagnostic accuracy for each pathology of SelectStitch was compared with accuracy when reviewing the entire video clip and when reviewing the Stitch image. Results There were no significant differences in diagnostic accuracy for physicians reviewing SelectStitch images and full video clips, but both provided better diagnostic accuracy than Stitch images. The inter-reader agreement was moderate. Conclusions Equal to using full video clips, composite images of eardrums generated by SelectStitch provided sufficient information for ENTs to make the correct diagnoses for most pathologies. These findings suggest that use of a composite eardrum image may be sufficient for telemedicine approaches to ear diagnosis, eliminating the need for storage and transmission of large video files, along with future applications for improved documentation in electronic medical record systems, patient/family counseling, and clinical training. Level of evidence 3 Laryngoscope, 2020.
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digital Otoscopy videos versus composite images a reader study to compare the accuracy of ent physicians
medRxiv, 2020Co-Authors: Hamidullah Binol, Theodoros N Teknos, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Khalid Khan M Niazi, Jay Shah, Jameson K Mattingly, Michael S Harris, Metin N GurcanAbstract:Objectives: With the increasing emphasis on developing effective telemedicine approaches in Otolaryngology, this study explored whether a single composite image stitched from a digital Otoscopy video provides acceptable diagnostic information to make an accurate diagnosis, as compared with that provided by the full video. Methods: Five Ear, Nose, and Throat (ENT) physicians reviewed the same set of 78 digital otoscope eardrum videos from four eardrum conditions: normal, effusion, retraction, and tympanosclerosis, along with the composite images generated by a SelectStitch method that selectively uses video frames with computer-assisted selection, as well as a Stitch method that incorporates all the video frames. Participants provided a diagnosis for each item along with a rating of diagnostic confidence. Diagnostic accuracy for each pathology of SelectStitch was compared with accuracy when reviewing the entire video clip and when reviewing the Stitch image. Results: There were no significant differences in diagnostic accuracy for physicians reviewing SelectStitch images and full video clips, but both provided better diagnostic accuracy than Stitch images. The inter-reader agreement was moderate. Conclusion: Equal to using full video clips, composite images of eardrums generated by SelectStitch provided sufficient information for ENTs to make the correct diagnoses for most pathologies. These findings suggest that use of a composite eardrum image may be sufficient for telemedicine approaches to ear diagnosis, eliminating the need for storage and transmission of large video files, along with future applications for improved documentation in electronic medical record systems, patient/family counseling, and clinical training.
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autoscope automated Otoscopy image analysis to diagnose ear pathology and use of clinically motivated eardrum features
Proceedings of SPIE, 2017Co-Authors: Caglar Senaras, Aaron C Moberly, Theodoros N Teknos, Garth F Essig, Charles A Elmaraghy, Nazhat Tajschaal, Metin N GurcanAbstract:In this study, we propose an automated Otoscopy image analysis system called Autoscope. To the best of our knowledge, Autoscope is the first system designed to detect a wide range of eardrum abnormalities by using high-resolution otoscope images and report the condition of the eardrum as “normal” or “abnormal.” In order to achieve this goal, first, we developed a preprocessing step to reduce camera-specific problems, detect the region of interest in the image, and prepare the image for further analysis. Subsequently, we designed a new set of clinically motivated eardrum features (CMEF). Furthermore, we evaluated the potential of the visual MPEG-7 descriptors for the task of tympanic membrane image classification. Then, we fused the information extracted from the CMEF and state-of-the-art computer vision features (CVF), which included MPEG-7 descriptors and two additional features together, using a state of the art classifier. In our experiments, 247 tympanic membrane images with 14 different types of abnormality were used, and Autoscope was able to classify the given tympanic membrane images as normal or abnormal with 84.6% accuracy.
