ingest cdrApp 2017-07-05T19:59:59.301Z d36eae88-cb6b-42c1-ba08-197eadfa9868 modifyDatastreamByValue RELS-EXT fedoraAdmin 2017-07-05T20:01:25.706Z Setting exclusive relation modifyDatastreamByValue RELS-EXT fedoraAdmin 2017-07-05T20:01:34.018Z Setting exclusive relation addDatastream MD_TECHNICAL fedoraAdmin 2017-07-05T20:01:42.247Z Adding technical metadata derived by FITS modifyDatastreamByValue RELS-EXT fedoraAdmin 2017-07-05T20:01:58.710Z Setting exclusive relation addDatastream MD_FULL_TEXT fedoraAdmin 2017-07-05T20:02:07.848Z Adding full text metadata extracted by Apache Tika modifyDatastreamByValue RELS-EXT fedoraAdmin 2017-07-05T20:02:16.929Z Setting exclusive relation modifyDatastreamByValue RELS-EXT cdrApp 2017-07-06T11:39:15.712Z Setting exclusive relation modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2017-09-07T13:01:27.906Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-01-25T13:29:03.269Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-01-27T13:29:31.049Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-02-28T16:28:33.341Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-03-14T10:45:19.211Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-05-18T13:28:57.179Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-07-11T09:13:47.501Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-07-18T05:18:42.047Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-08-16T18:25:57.075Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-09-27T14:09:02.818Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-10-12T05:24:40.034Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2019-03-21T15:13:35.152Z Peter Mueller Author Joint Department of Biomedical Engineering College of Arts and Sciences Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. Spring 2017 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text Peter Mueller Author Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. Spring 2017 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text Peter Mueller Creator Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. Spring 2017 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text Peter Mueller Creator Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. Spring 2017 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text Peter Mueller Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. Spring 2017 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text Peter Mueller Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. 2017-05 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Masters Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text Peter Mueller Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Masters Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text 2017-05 Peter Mueller Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Masters Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text 2017-05 Peter Mueller Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Masters Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text 2017-05 Peter Mueller Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Masters Thesis Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text 2017-05 University of North Carolina at Chapel Hill Degree granting institution Peter Mueller Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. 2017 Biomedical engineering Medical imaging Active Contours; Burns; Dermatology; Image Segmentation; Medical Imaging; Wound Imaging eng Master of Science Masters Thesis Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text 2017-05 University of North Carolina at Chapel Hill Degree granting institution Peter Mueller Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Development and Analysis of Dermal Wound Image Processing Techniques Using Chan-Vese and Edge Active Contour Methods Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. 2017 Biomedical engineering Medical imaging Active Contours, Burns, Dermatology, Image Segmentation, Medical Imaging, Wound Imaging eng Master of Science Masters Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Biomedical Engineering Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text 2017-05 Peter Mueller Creator UNC/NCSU Joint Department of Biomedical Engineering School of Medicine Present methods for evaluation of burn wounds rely heavily on qualitative and Total Body Surface Area (TBSA) estimations. Herein, a digital method for calculating the surface area of burn wounds is proposed as a useful tool for monitoring and measuring changes in burns. This study tested two segmentation methods: a statistical analysis technique, and an active contours technique using edges and Chan-Vese. All methods were tested on images of burns taken from a DSLR camera, and Microsoft Kinect V2 and compared to digitally drawn traces of the wounds. Using Dice’s Coefficient as a measure for agreement between masks, the DSLR images resulted in agreeable segmentations (D=0.939 for edge, D=0.9362 for Chan-Vese), while images taken with the Kinect did not meet the threshold for agreeability (D=0.815 for edge, D=0.819 for Chan-Vese). This testing shows the active contours method is the plausible method for characterizing high-resolution color burn wounds. 2017 Biomedical engineering Medical imaging Active Contours; Burns; Dermatology; Image Segmentation; Medical Imaging; Wound Imaging eng Master of Science Masters Thesis University of North Carolina at Chapel Hill Graduate School Degree granting institution Devin Hubbard Thesis advisor Dwight Walker Thesis advisor Shawn Gomez Thesis advisor Gianmarco Pinton Thesis advisor text 2017-05 Mueller_unc_0153M_17049.pdf uuid:05a2e49f-eaf6-4571-9c22-bfd1d22b134b 2019-07-05T00:00:00 2017-04-19T16:05:32Z proquest application/pdf 2361239 yes