Zobrazeno 1 - 10
of 116
pro vyhledávání: '"Mehrtash, Alireza"'
Autor:
Lucassen, Ruben T., Jafari, Mohammad H., Duggan, Nicole M., Jowkar, Nick, Mehrtash, Alireza, Fischetti, Chanel, Bernier, Denie, Prentice, Kira, Duhaime, Erik P., Jin, Mike, Abolmaesumi, Purang, Heslinga, Friso G., Veta, Mitko, Duran-Mendicuti, Maria A., Frisken, Sarah, Shyn, Paul B., Golby, Alexandra J., Boyer, Edward, Wells, William M., Goldsmith, Andrew J., Kapur, Tina
Lung ultrasound (LUS) is an important imaging modality used by emergency physicians to assess pulmonary congestion at the patient bedside. B-line artifacts in LUS videos are key findings associated with pulmonary congestion. Not only can the interpre
Externí odkaz:
http://arxiv.org/abs/2302.07844
Autor:
Mehrtash, Alireza, Ziegler, Erik, Idris, Tagwa, Somarouthu, Bhanusupriya, Urban, Trinity, LaCasce, Ann S., Jacene, Heather, Van Den Abbeele, Annick D., Pieper, Steve, Harris, Gordon, Kikinis, Ron, Kapur, Tina
Publikováno v:
In Computerized Medical Imaging and Graphics January 2024 111
Autor:
Mehrtash, Alireza
In the past twenty years, the combination of the advances in medical imaging technologies and therapeutic methods had a great impact in developing minimally invasive interventional procedures. Although the use of medical imaging for the surgery and t
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-248042
Autor:
Mehrtash, Alireza, Abolmaesumi, Purang, Golland, Polina, Kapur, Tina, Wassermann, Demian, Wells III, William M.
Ensembling is now recognized as an effective approach for increasing the predictive performance and calibration of deep networks. We introduce a new approach, Parameter Ensembling by Perturbation (PEP), that constructs an ensemble of parameter values
Externí odkaz:
http://arxiv.org/abs/2010.12721
Autor:
Mehrtash, Alireza, Wells III, William M., Tempany, Clare M., Abolmaesumi, Purang, Kapur, Tina
Fully convolutional neural networks (FCNs), and in particular U-Nets, have achieved state-of-the-art results in semantic segmentation for numerous medical imaging applications. Moreover, batch normalization and Dice loss have been used successfully t
Externí odkaz:
http://arxiv.org/abs/1911.13273
Autor:
Rouhollahi, Amir, Willi, James Noel, Haltmeier, Sandra, Mehrtash, Alireza, Straughan, Ross, Javadikasgari, Hoda, Brown, Jonathan, Itoh, Akinobu, de la Cruz, Kim I., Aikawa, Elena, Edelman, Elazer R., Nezami, Farhad R.
Publikováno v:
In Computerized Medical Imaging and Graphics October 2023 109
Autor:
Kuijf, Hugo J., Biesbroek, J. Matthijs, de Bresser, Jeroen, Heinen, Rutger, Andermatt, Simon, Bento, Mariana, Berseth, Matt, Belyaev, Mikhail, Cardoso, M. Jorge, Casamitjana, Adrià, Collins, D. Louis, Dadar, Mahsa, Georgiou, Achilleas, Ghafoorian, Mohsen, Jin, Dakai, Khademi, April, Knight, Jesse, Li, Hongwei, Lladó, Xavier, Luna, Miguel, Mahmood, Qaiser, McKinley, Richard, Mehrtash, Alireza, Ourselin, Sébastien, Park, Bo-yong, Park, Hyunjin, Park, Sang Hyun, Pezold, Simon, Puybareau, Elodie, Rittner, Leticia, Sudre, Carole H., Valverde, Sergi, Vilaplana, Verónica, Wiest, Roland, Xu, Yongchao, Xu, Ziyue, Zeng, Guodong, Zhang, Jianguo, Zheng, Guoyan, Chen, Christopher, van der Flier, Wiesje, Barkhof, Frederik, Viergever, Max A., Biessels, Geert Jan
Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are often still obtained from manual segmentations on brain MR images, whic
Externí odkaz:
http://arxiv.org/abs/1904.00682
Autor:
Sedghi, Alireza, Luo, Jie, Mehrtash, Alireza, Pieper, Steve, Tempany, Clare M., Kapur, Tina, Mousavi, Parvin, Wells III, William M.
This paper establishes an information theoretic framework for deep metric based image registration techniques. We show an exact equivalence between maximum profile likelihood and minimization of joint entropy, an important early information theoretic
Externí odkaz:
http://arxiv.org/abs/1901.00040
Autor:
Sedghi, Alireza, Luo, Jie, Mehrtash, Alireza, Pieper, Steve, Tempany, Clare M., Kapur, Tina, Mousavi, Parvin, Wells III, William M.
Deep metrics have been shown effective as similarity measures in multi-modal image registration; however, the metrics are currently constructed from aligned image pairs in the training data. In this paper, we propose a strategy for learning such metr
Externí odkaz:
http://arxiv.org/abs/1804.01565
Autor:
Ghafoorian, Mohsen, Mehrtash, Alireza, Kapur, Tina, Karssemeijer, Nico, Marchiori, Elena, Pesteie, Mehran, Guttmann, Charles R. G., de Leeuw, Frank-Erik, Tempany, Clare M., van Ginneken, Bram, Fedorov, Andriy, Abolmaesumi, Purang, Platel, Bram, Wells III, William M.
Publikováno v:
Medical Image Computing and Computer-Assisted Intervention 2017, Vol 10435, 516-524
Magnetic Resonance Imaging (MRI) is widely used in routine clinical diagnosis and treatment. However, variations in MRI acquisition protocols result in different appearances of normal and diseased tissue in the images. Convolutional neural networks (
Externí odkaz:
http://arxiv.org/abs/1702.07841