Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Sinan Kockara"'
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S2, Pp 87-97 (2019)
Abstract Background Dermoscopy is one of the common and effective imaging techniques in diagnosis of skin cancer, especially for pigmented lesions. Accurate skin lesion border detection is the key to extract important dermoscopic features of the skin
Externí odkaz:
https://doaj.org/article/9256040d6f254b2dab44cd0b2a5e5d46
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S2, Pp 99-114 (2019)
Abstract Background This paper presents a novel approach for Generative Anatomy Modeling Language (GAML). This approach automatically detects the geometric partitions in 3D anatomy that in turn speeds up integrated non-linear optimization model in GA
Externí odkaz:
https://doaj.org/article/6adb07f9a80440339f11c9b9e4c531b9
Publikováno v:
BMC Bioinformatics, Vol 18, Iss S14, Pp 51-60 (2017)
Abstract Background Abruptness of pigment patterns at the periphery of a skin lesion is one of the most important dermoscopic features for detection of malignancy. In current clinical setting, abrupt cutoff of a skin lesion determined by an examinati
Externí odkaz:
https://doaj.org/article/4c95e034beba4baf82eeb2d7bd42878f
Autor:
Doga Demirel, Bryce Palmer, Gunnar Sundberg, Bayazit Karaman, Tansel Halic, Sinan Kockara, Nizamettin Kockara, Mark Edward Rogers, Shahryar Ahmadi
Publikováno v:
Int J Comput Assist Radiol Surg
PURPOSE: We aim to develop quantitative performance metrics and a deep learning model to objectively assess surgery skills between the novice and the expert surgeons for arthroscopic rotator cuff surgery. These proposed metrics can be used to give th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c603bde8c866d1d5cfc3616360f46924
https://doi.org/10.1007/s11548-022-02683-3
https://doi.org/10.1007/s11548-022-02683-3
Autor:
Shahryar Ahmadi, Venkata Sreekanth Arikatla, Kevin W. Sexton, Tansel Halic, Seema Shedage, Sinan Kockara, Doga Demirel, Jake Farmer
Publikováno v:
2021 the 5th International Conference on Information System and Data Mining.
Minimally invasive skills assessment is important in developing competent surgical simulators and executing reliable skills evaluation [9]. Arthroscopy and Laparoscopy surgeries are considered Minimally Invasive Surgeries (MIS). In MIS, the surgeon o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2dff86e37f849713cf147e9aca65ae0
https://doi.org/10.1145/3471287.3471296
https://doi.org/10.1145/3471287.3471296
Autor:
Jake Farmer, Tansel Halic, Mustafa Tunc, Doga Demirel, Sinan Kockara, Daniel Ahmadi, Sreekanth Arikatla, Shahryar Ahmadi
Publikováno v:
ICISDM
This works presents a design and development of Virtual Rotator Cuff Arthroscopic Skill Trainer (ViRCAST) and its preliminary subject study analysis using machine learning approach. Arthroscopy is a minimally invasive surgical intervention regarded a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49d00e3524c21198eb16bc32ad9a6484
https://doi.org/10.1145/3404663.3404673
https://doi.org/10.1145/3404663.3404673
Autor:
Venkata Sreekanth Arikatla, Sinan Kockara, Jake Farmer, Shahryar Ahmadi, Kevin W. Sexton, Tansel Halic, Recep Erol, Daniel Ahmadi, Doga Demirel
Publikováno v:
Int J Med Robot
Background In minimally invasive surgery, there are several challenges for training novice surgeons, such as limited field-of-view and unintuitive hand-eye coordination due to performing the operation according to video feedback. Virtual reality (VR)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3f914a1f7115e76245934e3b7389c45
https://doi.org/10.1002/rcs.2105
https://doi.org/10.1002/rcs.2105
Autor:
Berk Cetinsaya, Dirk Reiners, Sreekanth Arikatla, Sinan Kockara, Shahryar Ahmadi, Tansel Halic, Doga Demirel
Publikováno v:
Comput Biol Med
Background This paper presents a novel iterative approach and rigorous accuracy testing for geometry modeling language - a Partition-based Optimization Model for Generative Anatomy Modeling Language (POM-GAML). POM-GAML is designed to model and creat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::451e722614159e85425ad77e3c6527a1
https://pubmed.ncbi.nlm.nih.gov/32339127
https://pubmed.ncbi.nlm.nih.gov/32339127
Publikováno v:
BMC Bioinformatics
BMC Bioinformatics, Vol 20, Iss S2, Pp 99-114 (2019)
BMC Bioinformatics, Vol 20, Iss S2, Pp 99-114 (2019)
Background This paper presents a novel approach for Generative Anatomy Modeling Language (GAML). This approach automatically detects the geometric partitions in 3D anatomy that in turn speeds up integrated non-linear optimization model in GAML for 3D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e6c6686f9ad3c035431cefa6a41f72a
http://europepmc.org/articles/PMC6419323
http://europepmc.org/articles/PMC6419323
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems. 26:3381-3393
This paper presents a massively parallel implementation of a prominent network clustering algorithm, the structural clustering algorithm for networks (SCAN), on a graphical processing unit (GPU). SCAN is a fast and efficient clustering technique for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::951dd5f52b58aa2973abc37d69c9d6cb
https://doi.org/10.1109/tpds.2014.2374607
https://doi.org/10.1109/tpds.2014.2374607