Medical Imaging: Computer-Aided Diagnosis

Keyphrases

Publications

2023

Keita Otani, Daiki Nishigaki, Taro Hatsutani, Takeshi Takamoto, Yuki Suzuki, Shoji Kido, Noriyuki Tomiyama
Automatic characterization of liver tumors from multi-phase CT images. 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)
John M. Hoffman, Frédéric Noo, Michael F. McNitt-Gray
An analytic, physics-based approach to scoring emphysema in lung CT patients. Medical Imaging: Computer-Aided Diagnosis (2023)
Mohsen Soltanpour, Muhammad Yousefnezhad, Russ Greiner, Pierre Boulanger, Brian Buck
Using temporal GAN to translate the current CTP scan to follow-up MRI, for predicting final acute ischemic stroke lesions. Medical Imaging: Computer-Aided Diagnosis (2023)
Tianyi Wang, Mingkai Li, Zebin Chen, Xi Chen, Haimei Chen, Bin Wu, Xiaoying Wu, Yue Li, Yao Lu
Tensor based multi-modality fusion for prediction of postoperative early recurrence of single hepatocellular carcinoma. 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)
Raissa Souza, Emma A. M. Stanley, Milton Camacho, Matthias Wilms, Nils D. Forkert
An analysis of intensity harmonization techniques for Parkinson's multi-site MRI datasets. Medical Imaging: Computer-Aided Diagnosis (2023)
Carolus H. J. Kusters, T. G. W. Boers, Jelmer B. Jukema, Martijn R. Jong, Kiki N. Fockens, Albert J. de Groof, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With
Real-time Barrett's neoplasia characterization in NBI videos using an int8-based quantized neural network. Medical Imaging: Computer-Aided Diagnosis (2023)
Jiabao Jin, Yu Wu, Gang Ding, Ying Ma, Hui-Qing Zeng, Sunkui Ke, Xiangxing Chen, Miao Wang, Yinran Chen, Xiongbiao Luo
Towards a relation extractor U-shaped network for accurate pulmonary vessel segmentation in CT images. Medical Imaging: Computer-Aided Diagnosis (2023)
Stepan Romanov, Sacha Howell, Elaine Harkness, Megan Bydder, D. Gareth Evans, Steven Squires, Martin Fergie, Susan M. Astley
Artificial intelligence for image-based breast cancer risk prediction using attention. Medical Imaging: Computer-Aided Diagnosis (2023)
Anneke Annassia Putri Siswadi, Stéphanie Bricq, Fabrice Mériaudeau
Multi-label ocular abnormalities detection with semantic dictionary learning. 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)
Francesco Marzola, Kristen M. Meiburger, Filippo Molinari, Massimo Salvi
Can multiple segmentation methods enhance deep learning networks generalization? A novel hybrid learning paradigm. 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)
Sanjana Mudduluru, Sai Kiran Reddy Maryada, William Booker, Dean F. Hougen, Bin Zheng
Improving medical image segmentation and classification using a novel joint deep learning model. Medical Imaging: Computer-Aided Diagnosis (2023)
Linnea Kremer, Boris Fosso, Lucy Groothuis, Arlene Chapman, Samuel G. Armato III
Radiomics-based classification of autosomal dominant polycystic kidney disease (ADPKD) Mayo imaging classification (MIC) and the effect of gray-level discretization. Medical Imaging: Computer-Aided Diagnosis (2023)
Abdelhamed Mohamed, Fabrice Mériaudeau
NesT UNet: pure transformer segmentation network with an application for automatic cardiac myocardial infarction evaluation. 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)
Mena Shenouda, Aditi Kaveti, Isabella Flerlage, Jayashree Kalpathy-Cramer, Maryellen L. Giger, Samuel G. Armato III
Assessing robustness of a deep-learning model for COVID-19 classification on chest radiographs. Medical Imaging: Computer-Aided Diagnosis (2023)
Mingzhe Hu, Jing Wang, Jacob F. Wynne, Tian Liu, Xiaofeng Yang
A vision-GNN framework for retinopathy classification using optical coherence tomography. Medical Imaging: Computer-Aided Diagnosis (2023)
Sjoerd A. M. Tunissen, Andrea Motta, Franziska Mauter, Eloy García, Oliver Díaz, John M. Boone, Ioannis Sechopoulos, Marco Caballo
End-to-end mammographic breast density quantification with deep learning: preliminary study on simulated mammograms. Medical Imaging: Computer-Aided Diagnosis (2023)
Chih-Chieh Liu, Qiulin Tang, Liang Cai, Zhou Yu, Jian Zhou
Automated right coronary artery localizer using deep learning for optimal cardiac phase selection. Medical Imaging: Computer-Aided Diagnosis (2023)
Chelsea E. Harris, Sokratis Makrogiannis
Breast mass characterization using sparse approximations of patch-sampled deep features. 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)
Antonio Tejero-de-Pablos, Hiroaki Yamane, Yusuke Kurose, Junichi Iho, Youji Tokunaga, Makoto Horie, Keisuke Nishizawa, Yusaku Hayashi, Yasushi Koyama, Tatsuya Harada
Improving segmentation of calcified and non-calcified plaques on CCTA-CPR scans via masking of the artery wall. Medical Imaging: Computer-Aided Diagnosis (2023)
Yoon Jo Kim, Min Jin Lee, Helen Hong, Sung Il Hwang
Deep regression model with ordinal and triplet loss for the prediction of prostate cancer aggressiveness in multi-parametric MR images. Medical Imaging: Computer-Aided Diagnosis (2023)
Apurva Singh, Hannah Horng, Leonid Roshkovan, Sharyn I. Katz, Despina Kontos, Jeffrey C. Thompson
Radiomics analysis to diagnose tumor invasiveness of pulmonary sub-solid nodules from longitudinal pre-surgical CT scans. Medical Imaging: Computer-Aided Diagnosis (2023)
Aman Kushwaha, Rami F. Mourad, Kevin Heist, Dariya I. Malyarenko, Heang-Ping Chan, Thomas L. Chenevert, Lubomir M. Hadjiiski
Segmentation of mouse tibia on MRI using deep learning U-Net models. 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)
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)
Aldir Sousa, Marcelo Toledo, José Eduardo Krieger, Marco Antonio Gutierrez
Automatic segmentation of stroke lesions in T1-weighted magnetic resonance images with convolutional neural networks. Medical Imaging: Computer-Aided Diagnosis (2023)
Nikhil Kumar Tomar, Ulas Bagci, Debesh Jha
RUPNet: residual upsampling network for real-time polyp segmentation. Medical Imaging: Computer-Aided Diagnosis (2023)
Kosuke Kita, Takahito Fujimori, Yuki Suzuki, Seiji Okada, Shoji Kido
Bi-modal network combining convolutional neural network and TabNet, differentiating spinal tumors based on images and clinical risk factors. Medical Imaging: Computer-Aided Diagnosis (2023)
Mohammadreza Zandehshahvar, Marly van Assen, Eun Young Kim, Yashar Kiarashi, Vikranth Keerthipati, Arthur E. Stillman, Peter Filev, Amir H. Davarpanah, Eugene A. Berkowitz, Stefan Tigges, Scott J. Lee, Brianna L. Vey, Carlo Nicola De Cecco, Ali Adibi
Bayesian neural networks for severity assessment of COVID-19 pneumonia from chest x-ray using a multi-reader and binational dataset. Medical Imaging: Computer-Aided Diagnosis (2023)
Ahmed G. Temtam, Liangsuo Ma, F. Gerard Moeller, Md. Shibly Sadique, Khan M. Iftekharuddin
Opioid use disorder prediction using machine learning of fMRI data. 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)
Sayantan Kumar, Philip R. O. Payne, Aristeidis Sotiras
Normative modeling using multimodal variational autoencoders to identify abnormal brain volume deviations in Alzheimer's disease. 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)
Md Belayat Hossain, Juhun Lee
Developing a task-oriented deep convolutional neural network application towards estimating near-term breast cancer risk: preliminary work. Medical Imaging: Computer-Aided Diagnosis (2023)
Hidenobu Suzuki, Yoshiki Kawata, Toshihiko Sugiura, Nobuhiro Tanabe, Yuji Matsumoto, Takaaki Tsuchida, Masahiko Kusumoto, Kazuyoshi Marumo, Masahiro Kaneko, Noboru Niki
Automated detection method of thoracic aorta calcification from non-contrast CT images using mediastinal anatomical label map. Medical Imaging: Computer-Aided Diagnosis (2023)
Rain Tarango, Lubomir M. Hadjiiski, Ajjai Alva, Heang-Ping Chan, Richard H. Cohan, Elaine M. Caoili, Kenny H. Cha, Ravi K. Samala, Alon Z. Weizer, Chuan Zhou, Monika Joshi, Yousef Zakharia
Survival prediction for patients with metastatic urothelial cancer after immunotherapy using machine learning. 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)
M. Ali Vosoughi, Akhil Kasturi, Nathan Hadjiyski, Axel Wismüller
Classification of schizophrenia using large-scale kernelized Granger causality (lsKGC) and functional MR imaging. Medical Imaging: Computer-Aided Diagnosis (2023)
Terese Hellström, Christiaan G. A. Viviers, Mark Ramaekers, Nick Tasios, Joost Nederend, Misha Luyer, Peter H. N. de With, Fons van der Sommen
Clinical segmentation for improved pancreatic ductal adenocarcinoma detection and segmentation. Medical Imaging: Computer-Aided Diagnosis (2023)
Stijn Vandewiele, Jonas De Vylder, Bart Diricx, Sandra Edward, Tom Kimpe
Open-source tool for model performance analysis for subpopulations. Medical Imaging: Computer-Aided Diagnosis (2023)
Alejandra Moreno, Andrea Rueda, Fabio Martínez
A volumetric multi-head attention strategy for lung nodule classification in CT. Medical Imaging: Computer-Aided Diagnosis (2023)
Jennie Karlsson, Ida Arvidsson, Freja Sahlin, Kalle Åström, Niels Christian Overgaard, Kristina Lång, Anders Heyden
Classification of point-of-care ultrasound in breast imaging using deep learning. Medical Imaging: Computer-Aided Diagnosis (2023)
Souvick Mukherjee, Cameron Duic, Tharindu De Silva, Tiarnan D. Keenan, Alisa T. Thavikulwat, Emily Y. Chew, Catherine Cukras
Drusen segmentation in color fundus photographs for drusenoid pigment epithelial detachment patients based on ground-truth derived from SD-OCTs. Medical Imaging: Computer-Aided Diagnosis (2023)
Ziyu Su, Sandhya Kumar, Thomas E. Tavolara, Metin N. Gurcan, Scott Segal, M. Khalid Khan Niazi
Predicting obstructive sleep apnea severity from craniofacial images using ensemble machine learning models. Medical Imaging: Computer-Aided Diagnosis (2023)

volume 12465, 2023

Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, CA, USA, February 19-23, 2023 Medical Imaging: Computer-Aided Diagnosis 12465 (2023)