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Publication search results
found 116 matches
- 2023
- João Vitor Alcantara, Joany Rodrigues, Paulo Rogério Julio, Simone Appenzeller, Letícia Rittner:
Volumetric corpus callosum segmentation integrated to inCCsight software for supporting DTI-based studies. Medical Imaging: Computer-Aided Diagnosis 2023 - Akshaya Anand, Jianfei Liu, Thomas C. Shen, W. Marston Linehan, Peter A. Pinto, Ronald M. Summers:
Automated classification of intravenous contrast enhancement phase of CT scans using residual networks. Medical Imaging: Computer-Aided Diagnosis 2023 - Katherine Aubert, Catherine Huber, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua:
Iterative K-means clustering for disease subtype discovery. Medical Imaging: Computer-Aided Diagnosis 2023 - Debayan Bhattacharya, Finn Behrendt, Benjamin Tobias Becker, Dirk Beyersdorff, Elina Petersen, Marvin Petersen, Bastian Cheng, Dennis Eggert, Christian Betz, Anna Sophie Hoffmann, Alexander Schlaefer:
Unsupervised anomaly detection of paranasal anomalies in the maxillary sinus. Medical Imaging: Computer-Aided Diagnosis 2023 - Moinak Bhattacharya, Prateek Prasanna:
Audio-visual feature fusion for improved thoracic disease classification. Medical Imaging: Computer-Aided Diagnosis 2023 - T. G. W. Boers, Carolus H. J. Kusters, Kiki N. Fockens, Jelmer B. Jukema, Martijn R. Jong, Jeroen de Groof, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With:
Barrett's lesion detection using a minimal integer-based neural network for embedded systems integration. Medical Imaging: Computer-Aided Diagnosis 2023 - Alexis Burgon, Nicholas Petrick, Berkman Sahiner, Gene Pennello, Ravi K. Samala:
Decision region analysis to deconstruct the subgroup influence on AI/ML predictions. Medical Imaging: Computer-Aided Diagnosis 2023 - Shanshan Cai, John Mai, Winn Hong, Scott Fraser, Francesco Cutrale:
Multiplexed diffused optical imaging generative adversarial network (mDOI-GAN) for sub-surface 3D imaging of tissues. Medical Imaging: Computer-Aided Diagnosis 2023 - Martha Rebeca Canales-Fiscal, José Gerardo Tamez-Peña:
Glaucoma classification using a morphological-convolutional neural network trained with extreme learning machine. Medical Imaging: Computer-Aided Diagnosis 2023 - Daniel Capellán-Martín, Juan J. Gómez-Valverde, Ramon Sánchez-Jacob, David Bermejo-Peláez, Lara García-Delgado, Elisa López-Varela, María J. Ledesma-Carbayo:
Deep learning-based lung segmentation and automatic regional template in chest x-ray images for pediatric tuberculosis. Medical Imaging: Computer-Aided Diagnosis 2023 - Satrajit Chakrabarty, Pamela LaMontagne, Joshua S. Shimony, Daniel S. Marcus, Aristeidis Sotiras:
Non-invasive classification of IDH mutation status of gliomas from multi-modal MRI using a 3D convolutional neural network. Medical Imaging: Computer-Aided Diagnosis 2023 - Tricia Chinnery, Pencilla Lang, Anthony Nichols, Sarah A. Mattonen:
Predicting the need for a replan in oropharyngeal cancer: a radiomic, clinical, and dosimetric model. Medical Imaging: Computer-Aided Diagnosis 2023 - Dabbara Keshava Chowdari, Nunna Radhasyam, Anabik Pal, Angshuman Paul:
Federated learning using multi-institutional data for generalizable chest x-ray diagnosis. Medical Imaging: Computer-Aided Diagnosis 2023 - Jonathan Clever, Lubomir M. Hadjiiski, Heang-Ping Chan, Richard H. Cohan, Elaine M. Caoili, Kenny H. Cha, Ravi Samala, Chuan Zhou:
Bladder cancer segmentation using U-Net-based deep-learning. Medical Imaging: Computer-Aided Diagnosis 2023 - Edoardo Coppola, Damiano Ferrari, Mattia Savardi, Alberto Signoroni:
Explainable AI for COVID-19 prognosis from early chest x-ray and clinical data in the context of the COVID-CXR international hackathon. Medical Imaging: Computer-Aided Diagnosis 2023 - J. L. Cozzi, Hui Li, Julian Conn Busch, J. Williams, Li Lan, X. Keutgen, Maryellen L. Giger:
Novel integration of radiomics and deep transfer learning for diagnosis of indeterminate thyroid nodules on ultrasound. Medical Imaging: Computer-Aided Diagnosis 2023 - Saba Dadsetan, Marcio Albers, Allison Weinstock, Volker Musahl, Gene Kitamura, Dooman Arefan, Shandong Wu:
Anterior cruciate ligament classification in knee MRI using automated pseudo-masking. Medical Imaging: Computer-Aided Diagnosis 2023 - Nikoo Dehghani, Thom Scheeve, T. G. W. Boers, Quirine E. W. van der Zander, Ayla Thijssen, Ramon-Michel Schreuder, Ad A. M. Masclee, Erik J. Schoon, Fons van der Sommen, Peter H. N. de With:
Effect of domain-specific self-supervised pretraining on predictive uncertainty for colorectal polyp characterization. Medical Imaging: Computer-Aided Diagnosis 2023 - Lara Dular, Gregor Brecl-Jakob, Lina Savsek, Jozef Magdic, Ziga Spiclin:
Predicting future multiple sclerosis disease progression from MR scans. Medical Imaging: Computer-Aided Diagnosis 2023 - Chelsea A. S. Dunning, Prabhakar Shantha Rajiah, Scott S. Hsieh, Andrea Esquivel, Mariana Yalon, Nikkole M. Weber, Hao Gong, Joel G. Fletcher, Cynthia H. McCollough, Shuai Leng:
Classification of high-risk coronary plaques using radiomic analysis of multi-energy photon-counting-detector computed tomography (PCD-CT) images. Medical Imaging: Computer-Aided Diagnosis 2023 - Behnaz Elhaminia, Alexandra Gilbert, Alejandro F. Frangi, Andrew F. Scarsbrook, John Lilley, Ane Appelt, Ali Gooya:
Deep learning with visual explanation for radiotherapy-induced toxicity prediction. Medical Imaging: Computer-Aided Diagnosis 2023 - Catalin I. Fetita, Antoine Didier, Jean Richeux, Christian Tulvan, Jean-François Bernaudin, Pierre-Yves Brillet, Aurélien Justet:
Linking CT and SPECT based analysis for quantitative follow-up of vascular perfusion defects in COVID-19. Medical Imaging: Computer-Aided Diagnosis 2023 - Jared Frazier, Tejas Sudharshan Mathai, Jianfei Liu, Angshuman Paul, Ronald M. Summers:
3D universal lesion detection and tagging in CT with self-training. Medical Imaging: Computer-Aided Diagnosis 2023 - Rohini Gaikar, Azar Azad, Nicola Schieda, Eranga Ukwatta:
Fully automated cascaded approach for renal mass detection on T2 weighted MRI images. Medical Imaging: Computer-Aided Diagnosis 2023 - Yongfeng Gao, Shaojie Chang, Marc Jason Pomeroy, Lihong Li, Zhengrong Liang:
Using virtual monoenergetic images in Karhunen-Loève domain to differentiate lesion pathology. Medical Imaging: Computer-Aided Diagnosis 2023 - Long Gao, Chang Liu, Dooman Arefan, Ashok Panigrahy, Margarita L. Zuley, Shandong Wu:
Medical knowledge-guided deep learning for mammographic breast density classification. Medical Imaging: Computer-Aided Diagnosis 2023 - Soumyendu Sekhar Ghosh, Rajat Dhar, Daniel S. Marcus, Aristeidis Sotiras:
Siam-VAE: a hybrid deep learning based anomaly detection framework for automated quality control of head CT scans. Medical Imaging: Computer-Aided Diagnosis 2023 - Shuyue Guan, Ravi K. Samala, Arian Arab, Weijie Chen:
MISS-tool: medical image segmentation synthesis tool to emulate segmentation errors. Medical Imaging: Computer-Aided Diagnosis 2023 - Lin Guo, Kunlei Hong, Ziqi Zhang, Bin Zheng, Stefan Jaeger, Jordan D. Fuhrman, Hui Li, Maryellen L. Giger, Andrei Gabrielian, Alex Rosenthal, Darrell E. Hurt, Ziv Yaniv, Y. M. Fleming Lure:
Assessing an AI-based smart imagery framing and truthing (SIFT) system to assist radiologists annotating lung abnormalities on chest x-ray images for development of deep learning models. Medical Imaging: Computer-Aided Diagnosis 2023 - Nathan Hadjiyski, M. Ali Vosoughi, Axel Wismüller:
Cross modal global local representation learning from radiology reports and x-ray chest images. Medical Imaging: Computer-Aided Diagnosis 2023
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