Výsledky vyhľadávania - "Image Processing Computer-Assisted"

Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors Autor Quattrini, Giulia, Pievani, Michela, Jovicich, Jorge, Aiello, Marco, Bargalló, Núria, Barkhof, Frederik, Bartres-Faz, David, Beltramello, Alberto, Pizzini, Francesca B., Blin, Olivier, Bordet, Regis, Caulo, Massimo, Constantinides, Manos, Didic, Mira, Drevelegas, Antonios, Ferretti, Antonio, Fiedler, Ute, Floridi, Piero, Gros-Dagnac, Hélène, Hensch, Tilman, Hoffmann, Karl-Titus, Kuijer, Joost P., Lopes, Renaud, Marra, Camillo, Müller, Bernhard W., Nobili, Flavio, Parnetti, Lucilla, Payoux, Pierre, Picco, Agnese, Ranjeva, Jean-Philippe, Roccatagliata, Luca, Rossini, Paolo M., Salvatore, Marco, Schonknecht, Peter, Schott, Björn H., Sein, Julien, Soricelli, Andrea, Tarducci, Roberto, Tsolaki, Magda, Visser, Pieter J., Wiltfang, Jens, Richardson, Jill C., Frisoni, Giovanni B., Marizzoni, Moira

“…The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of…”
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What’s new and what’s next in diffusion MRI preprocessing Autor Tax, Chantal M.W., Bastiani, Matteo, Veraart, Jelle, Garyfallidis, Eleftherios, Okan Irfanoglu, M.

“…•This review covers diffusion MRI artifacts and preprocessing steps.•Notable developments and new advances since the HCP are summarized.•Practical…”
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Deep learning on image denoising: An overview Autor Tian, Chunwei, Fei, Lunke, Zheng, Wenxian, Xu, Yong, Zuo, Wangmeng, Lin, Chia-Wen

“…Deep learning techniques have received much attention in the area of image denoising. However, there are substantial differences in the various types of deep…”
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Guidelines for the content and format of PET brain data in publications and archives: A consensus paper Autor Knudsen, Gitte M, Ganz, Melanie, Appelhoff, Stefan, Boellaard, Ronald, Bormans, Guy, Carson, Richard E, Catana, Ciprian, Doudet, Doris, Gee, Antony D, Greve, Douglas N, Gunn, Roger N, Halldin, Christer, Herscovitch, Peter, Huang, Henry, Keller, Sune H, Lammertsma, Adriaan A, Lanzenberger, Rupert, Liow, Jeih-San, Lohith, Talakad G, Lubberink, Mark, Lyoo, Chul H, Mann, J John, Matheson, Granville J, Nichols, Thomas E, Nørgaard, Martin, Ogden, Todd, Parsey, Ramin, Pike, Victor W, Price, Julie, Rizzo, Gaia, Rosa-Neto, Pedro, Schain, Martin, Scott, Peter Jh, Searle, Graham, Slifstein, Mark, Suhara, Tetsuya, Talbot, Peter S, Thomas, Adam, Veronese, Mattia, Wong, Dean F, Yaqub, Maqsood, Zanderigo, Francesca, Zoghbi, Sami, Innis, Robert B

“…It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging…”
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Deep learning extended depth-of-field microscope for fast and slide-free histology Autor Jin, Lingbo, Tang, Yubo, Wu, Yicheng, Coole, Jackson B, Tan, Melody T, Zhao, Xuan, Badaoui, Hawraa, Robinson, Jacob T, Williams, Michelle D, Gillenwater, Ann M, Richards-Kortum, Rebecca R, Veeraraghavan, Ashok

“…Microscopic evaluation of resected tissue plays a central role in the surgical management of cancer. Because optical microscopes have a limited depth-of-field…”
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The ImageJ ecosystem: An open platform for biomedical image analysis Autor Schindelin, Johannes, Rueden, Curtis T., Hiner, Mark C., Eliceiri, Kevin W.

“…SUMMARY Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which…”
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A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI Autor Tjoa, Erico, Guan, Cuntai

“…Recently, artificial intelligence and machine learning in general have demonstrated remarkable performances in many tasks, from image processing to natural…”
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Whole Slide Imaging: Technology and Applications Autor Hanna, Matthew G, Parwani, Anil, Sirintrapun, Sahussapont Joseph

“…Pathology has benefited from advanced innovation with novel technology to implement a digital solution. Whole slide imaging is a disruptive technology where…”
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Boundary-aware context neural network for medical image segmentation Autor Wang, Ruxin, Chen, Shuyuan, Ji, Chaojie, Fan, Jianping, Li, Ye

“…•Propose a boundary-aware context neural network for 2D medical image segmentation.•The pyramid edge extraction module aggregates edge information with…”
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The challenge of mapping the human connectome based on diffusion tractography Autor Maier-Hein, Klaus H., Neher, Peter F., Houde, Jean-Christophe, Côté, Marc-Alexandre, Garyfallidis, Eleftherios, Zhong, Jidan, Chamberland, Maxime, Yeh, Fang-Cheng, Lin, Ying-Chia, Ji, Qing, Reddick, Wilburn E., Glass, John O., Chen, David Qixiang, Feng, Yuanjing, Gao, Chengfeng, Wu, Ye, Ma, Jieyan, He, Renjie, Li, Qiang, Westin, Carl-Fredrik, Deslauriers-Gauthier, Samuel, González, J. Omar Ocegueda, Paquette, Michael, St-Jean, Samuel, Girard, Gabriel, Rheault, François, Sidhu, Jasmeen, Tax, Chantal M. W., Guo, Fenghua, Mesri, Hamed Y., Dávid, Szabolcs, Froeling, Martijn, Heemskerk, Anneriet M., Leemans, Alexander, Boré, Arnaud, Pinsard, Basile, Bedetti, Christophe, Desrosiers, Matthieu, Brambati, Simona, Doyon, Julien, Sarica, Alessia, Vasta, Roberta, Cerasa, Antonio, Quattrone, Aldo, Yeatman, Jason, Khan, Ali R., Hodges, Wes, Alexander, Simon, Romascano, David, Barakovic, Muhamed, Auría, Anna, Esteban, Oscar, Lemkaddem, Alia, Thiran, Jean-Philippe, Cetingul, H. Ertan, Odry, Benjamin L., Mailhe, Boris, Nadar, Mariappan S., Pizzagalli, Fabrizio, Prasad, Gautam, Villalon-Reina, Julio E., Galvis, Justin, Thompson, Paul M., Requejo, Francisco De Santiago, Laguna, Pedro Luque, Lacerda, Luis Miguel, Barrett, Rachel, Dell’Acqua, Flavio, Catani, Marco, Petit, Laurent, Caruyer, Emmanuel, Daducci, Alessandro, Dyrby, Tim B., Holland-Letz, Tim, Hilgetag, Claus C., Stieltjes, Bram, Descoteaux, Maxime

“…Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically…”
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Cross-validation failure: Small sample sizes lead to large error bars Autor Varoquaux, Gaël

“…Predictive models ground many state-of-the-art developments in statistical brain image analysis: decoding, MVPA, searchlight, or extraction of biomarkers. The…”
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The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges Autor Liu, Zhenyu, Wang, Shuo, Dong, Di, Wei, Jingwei, Fang, Cheng, Zhou, Xuezhi, Sun, Kai, Li, Longfei, Li, Bo, Wang, Meiyun, Tian, Jie

“…Medical imaging can assess the tumor and its environment in their entirety, which makes it suitable for monitoring the temporal and spatial characteristics of…”
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Radiomics: from qualitative to quantitative imaging Autor Rogers, William, Thulasi Seetha, Sithin, Refaee, Turkey A. G., Lieverse, Relinde I. Y., Granzier, Renée W. Y., Ibrahim, Abdalla, Keek, Simon A., Sanduleanu, Sebastian, Primakov, Sergey P., Beuque, Manon P. L., Marcus, Damiënne, van der Wiel, Alexander M. A., Zerka, Fadila, Oberije, Cary J. G., van Timmeren, Janita E, Woodruff, Henry C., Lambin, Philippe

“…Historically, medical imaging has been a qualitative or semi-quantitative modality. It is difficult to quantify what can be seen in an image, and to turn it…”
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Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists Autor Haenssle, H A, Fink, C, Schneiderbauer, R, Toberer, F, Buhl, T, Blum, A, Kalloo, A, Hassen, A Ben Hadj, Thomas, L, Enk, A, Uhlmann, L, Alt, Christina, Arenbergerova, Monika, Bakos, Renato, Baltzer, Anne, Bertlich, Ines, Blum, Andreas, Bokor-Billmann, Therezia, Bowling, Jonathan, Braghiroli, Naira, Braun, Ralph, Buder-Bakhaya, Kristina, Buhl, Timo, Cabo, Horacio, Cabrijan, Leo, Cevic, Naciye, Classen, Anna, Deltgen, David, Fink, Christine, Georgieva, Ivelina, Hakim-Meibodi, Lara-Elena, Hanner, Susanne, Hartmann, Franziska, Hartmann, Julia, Haus, Georg, Hoxha, Elti, Karls, Raimonds, Koga, Hiroshi, Kreusch, Jürgen, Lallas, Aimilios, Majenka, Pawel, Marghoob, Ash, Massone, Cesare, Mekokishvili, Lali, Mestel, Dominik, Meyer, Volker, Neuberger, Anna, Nielsen, Kari, Oliviero, Margaret, Pampena, Riccardo, Paoli, John, Pawlik, Erika, Rao, Barbar, Rendon, Adriana, Russo, Teresa, Sadek, Ahmed, Samhaber, Kinga, Schneiderbauer, Roland, Schweizer, Anissa, Toberer, Ferdinand, Trennheuser, Lukas, Vlahova, Lyobomira, Wald, Alexander, Winkler, Julia, Wölbing, Priscila, Zalaudek, Iris

“…Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of…”
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Artificial intelligence in breast imaging Autor Le, E.P.V., Wang, Y., Huang, Y., Hickman, S., Gilbert, F.J.

“…This article reviews current limitations and future opportunities for the application of computer-aided detection (CAD) systems and artificial intelligence in…”
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Embedded pupil function recovery for Fourier ptychographic microscopy Autor Ou, Xiaoze, Zheng, Guoan, Yang, Changhuei

“…We develop and test a pupil function determination algorithm, termed embedded pupil function recovery (EPRY), which can be incorporated into the Fourier…”
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Automated tilt series alignment and tomographic reconstruction in IMOD Autor Mastronarde, David N., Held, Susannah R.

“…Automated tomographic reconstruction is now possible in the IMOD software package, including the merging of tomograms taken around two orthogonal axes. Several…”
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Automated segmentation by deep learning of loose connective tissue fibers to define safe dissection planes in robot-assisted gastrectomy Autor Kumazu, Yuta, Kobayashi, Nao, Kitamura, Naoki, Rayan, Elleuch, Neculoiu, Paul, Misumi, Toshihiro, Hojo, Yudai, Nakamura, Tatsuro, Kumamoto, Tsutomu, Kurahashi, Yasunori, Ishida, Yoshinori, Masuda, Munetaka, Shinohara, Hisashi

“…The prediction of anatomical structures within the surgical field by artificial intelligence (AI) is expected to support surgeons’ experience and cognitive…”
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The first step for neuroimaging data analysis: DICOM to NIfTI conversion Autor Li, Xiangrui, Morgan, Paul S., Ashburner, John, Smith, Jolinda, Rorden, Christopher

“…•Introduce conversion tools for different vendors.•Explain conversion basics.•Present methods to detect and correctproblems. Clinical imaging data are…”
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Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank Autor Alfaro-Almagro, Fidel, Jenkinson, Mark, Bangerter, Neal K., Andersson, Jesper L.R., Griffanti, Ludovica, Douaud, Gwenaëlle, Sotiropoulos, Stamatios N., Jbabdi, Saad, Hernandez-Fernandez, Moises, Vallee, Emmanuel, Vidaurre, Diego, Webster, Matthew, McCarthy, Paul, Rorden, Christopher, Daducci, Alessandro, Alexander, Daniel C., Zhang, Hui, Dragonu, Iulius, Matthews, Paul M., Miller, Karla L., Smith, Stephen M.

“…UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing…”
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