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ORCIDMIUA 2021: Oxford, UK
- Bartlomiej W. Papiez, Mohammad Yaqub, Jianbo Jiao
, Ana I. L. Namburete, J. Alison Noble:
Medical Image Understanding and Analysis - 25th Annual Conference, MIUA 2021, Oxford, United Kingdom, July 12-14, 2021, Proceedings. Lecture Notes in Computer Science 12722, Springer 2021, ISBN 978-3-030-80431-2
Biomarker Detection
- Tamal Chowdhury, Angad R. S. Bajwa, Tapabrata Chakraborti, Jens Rittscher, Umapada Pal:
Exploring the Correlation Between Deep Learned and Clinical Features in Melanoma Detection. 3-17 - Yu Yang, Zijian Zhao, Pan Shi, Sanyuan Hu:
An Efficient One-Stage Detector for Real-Time Surgical Tools Detection in Robot-Assisted Surgery. 18-29 - Jarred Orfao, Dustin van der Haar:
A Comparison of Computer Vision Methods for the Combined Detection of Glaucoma, Diabetic Retinopathy and Cataracts. 30-42 - Liping Wang, Yuanjie Zheng, Andrik Rampun, Reyer Zwiggelaar:
Prostate Cancer Detection Using Image-Based Features in Dynamic Contrast Enhanced MRI. 43-55 - Zhe Min, Fernando J. Bianco, Qianye Yang, Rachael Rodell, Wen Yan, Dean C. Barratt, Yipeng Hu:
Controlling False Positive/Negative Rates for Deep-Learning-Based Prostate Cancer Detection on Multiparametric MR Images. 56-70 - Niamh Belton, Ivan Welaratne, Adil Dahlan, Ronan T. Hearne, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran:
Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability. 71-86 - Ziang Xu, Sharib Ali, Soumya Gupta, Numan Celik, Jens Rittscher:
Improved Artifact Detection in Endoscopy Imaging Through Profile Pruning. 87-97 - Dewmini Hasara Wickremasinghe, Natallia Khenkina, Pier-Giorgio Masci, Andrew P. King, Esther Puyol-Antón:
Automatic Detection of Extra-Cardiac Findings in Cardiovascular Magnetic Resonance. 98-107 - Suhita Karmakar, Dipayan Dewan, Lidia Ghosh, Abir Chowdhury, Amit Konar, Atulya K. Nagar:
Brain-Connectivity Analysis to Differentiate Phasmophobic and Non-phasmophobic: An EEG Study. 108-122
Image Registration, and Reconstruction
- Miguel Martínez-Albaladejo, Josep Sulé-Suso, David Lines, James Bisson, Simon Jassal, Craig Edwards:
Virtual Imaging for Patient Information on Radiotherapy Planning and Delivery for Prostate Cancer. 125-139 - Farnaz Khun Jush, Peter Michael Dueppenbecker, Andreas Maier:
Data-Driven Speed-of-Sound Reconstruction for Medical Ultrasound: Impacts of Training Data Format and Imperfections on Convergence. 140-150 - José Bernal, William Xu, Maria del C. Valdés Hernández, Javier Escudero, Angela C. C. Jochems, Una Clancy, Fergus N. Doubal, Michael S. Stringer, Michael J. Thrippleton, Rhian M. Touyz, Joanna M. Wardlaw:
Selective Motion Artefact Reduction via Radiomics and k-space Reconstruction for Improving Perivascular Space Quantification in Brain Magnetic Resonance Imaging. 151-164 - Marjola Thanaj, Nicolas Basty, Yi Liu, Madeleine Cule, Elena P. Sorokin, E. Louise Thomas, Jimmy D. Bell, Brandon J. Whitcher:
Mass Univariate Regression Analysis for Three-Dimensional Liver Image-Derived Phenotypes. 165-176 - Lindsay Munroe, Gina Sajith, Ei Lin, Surjava Bhattacharya, Kuberan Pushparajah, John M. Simpson, Julia A. Schnabel, Gavin Wheeler, Alberto Gómez, Shujie Deng:
Automatic Re-orientation of 3D Echocardiographic Images in Virtual Reality Using Deep Learning. 177-188 - Meysam Dadgar, Szymon Parzych, Faranak Tayefi Ardebili:
A Simulation Study to Estimate Optimum LOR Angular Acceptance for the Image Reconstruction with the Total-Body J-PET. 189-200 - Abhirup Banerjee, Ernesto Zacur, Robin P. Choudhury, Vicente Grau:
Optimised Misalignment Correction from Cine MR Slices Using Statistical Shape Model. 201-209 - Alexandre Triay Bagur, Paul Aljabar, Zobair Arya, John McGonigle, Michael Brady, Daniel Bulte:
Slice-to-Volume Registration Enables Automated Pancreas MRI Quantification in UK Biobank. 210-223
Image Segmentation
- Zobair Arya, Ged Ridgway, Arun Jandor, Paul Aljabar:
Deep Learning-Based Landmark Localisation in the Liver for Couinaud Segmentation. 227-237 - Darwon Rashid, Sophie Cai, Ylenia Giarratano, Calum D. Gray, Charlene Hamid, Dilraj S. Grewal, Tom J. MacGillivray, Sharon Fekrat, Cason B. Robbins, Srinath Soundararajan, Justin P. Ma, Miguel O. Bernabeu:
Reproducibility of Retinal Vascular Phenotypes Obtained with Optical Coherence Tomography Angiography: Importance of Vessel Segmentation. 238-249 - Shihfan Jack Tu, Jules Morel, Minsi Chen, Stephen J. Mellon:
Fast Automatic Bone Surface Segmentation in Ultrasound Images Without Machine Learning. 250-264 - James Owler, Alexandre Triay Bagur, Scott Marriage, Zobair Arya, Paul Aljabar, John McGonigle, Michael Brady, Daniel Bulte:
Pancreas Volumetry in UK Biobank: Comparison of Models and Inference at Scale. 265-279 - Evan Hann, Ricardo A. Gonzales, Iulia A. Popescu, Qiang Zhang, Vanessa M. Ferreira, Stefan K. Piechnik:
Ensemble of Deep Convolutional Neural Networks with Monte Carlo Dropout Sampling for Automated Image Segmentation Quality Control and Robust Deep Learning Using Small Datasets. 280-293 - Seoin Chai, Daniel Rueckert, Ahmed E. Fetit:
Reducing Textural Bias Improves Robustness of Deep Segmentation Models. 294-304
Generative Models, Biomedical Simulation and Modelling
- Songlin Hou, Clifford Lindsay, Emmanuel Agu, Peder C. Pedersen, Bengisu Tulu, Diane M. Strong:
HDR-Like Image Generation to Mitigate Adverse Wound Illumination Using Deep Bi-directional Retinex and Exposure Fusion. 307-321 - Ann-Katrin Thebille, Esther Dietrich, Martin Klaus, Lukas Gernhold, Maximilian Lennartz, Christoph Kuppe, Rafael Kramann, Tobias B. Huber, Guido Sauter, Victor G. Puelles, Marina Zimmermann, Stefan Bonn:
Deep Learning-Based Bias Transfer for Overcoming Laboratory Differences of Microscopic Images. 322-336 - Zixin Yang, Richard A. Simon, Yangming Li, Cristian A. Linte:
Dense Depth Estimation from Stereo Endoscopy Videos Using Unsupervised Optical Flow Methods. 337-349 - Ruizhe Li, Matteo Bastiani, Dorothee Auer, Christian Wagner, Xin Chen:
Image Augmentation Using a Task Guided Generative Adversarial Network for Age Estimation on Brain MRI. 350-360 - Elizaveta Savochkina, Lok Hin Lee, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble:
First Trimester Gaze Pattern Estimation Using Stochastic Augmentation Policy Search for Single Frame Saliency Prediction. 361-374
Classification
- Jun-En Ding, Chi-Hsiang Chu, Mong-Na Lo Huang, Chien-Ching Hsu:
Dopamine Transporter SPECT Image Classification for Neurodegenerative Parkinsonism via Diffusion Maps and Machine Learning Classifiers. 377-393 - Pankaj Pandey, Krishna Prasad Miyapuram:
BRAIN2DEPTH: Lightweight CNN Model for Classification of Cognitive States from EEG Recordings. 394-407 - Jian Han Lim, Chun Shui Tan, Chee Seng Chan, Roshan Alex Welikala, Paolo Remagnino, Senthilmani Rajendran, Thomas George Kallarakkal, Rosnah Binti Zain, Ruwan Duminda Jayasinghe, Jyotsna Rimal, Alexander Ross Kerr, Rahmi Amtha, Karthikeya Patil, Wanninayake Mudiyanselage Tilakaratne, John Gibson, Sok Ching Cheong, Sarah Ann Barman:
D'OraCa: Deep Learning-Based Classification of Oral Lesions with Mouth Landmark Guidance for Early Detection of Oral Cancer. 408-422 - Ali Eskandari, Hongbo Du, Alaa AlZoubi:
Towards Linking CNN Decisions with Cancer Signs for Breast Lesion Classification from Ultrasound Images. 423-437 - Mohammed Ahmed, Alaa AlZoubi, Hongbo Du:
Improving Generalization of ENAS-Based CNN Models for Breast Lesion Classification from Ultrasound Images. 438-453
Image Enhancement, Quality Assessment, and Data Privacy
- Manish Gawali, C. S. Arvind, Shriya Suryavanshi, Harshit Madaan, Ashrika Gaikwad, K. N. Bhanu Prakash, Viraj Kulkarni, Aniruddha Pant:
Comparison of Privacy-Preserving Distributed Deep Learning Methods in Healthcare. 457-471 - Thiago V. M. Lima, Silvan Melchior, Ismail Özden, Egbert Nitzsche, Jörg Binder, Gerd Lutters:
MAFIA-CT: MAchine Learning Tool for Image Quality Assessment in Computed Tomography. 472-487 - Robert B. Labs, Massoud Zolgharni, Jonathan P. Loo:
Echocardiographic Image Quality Assessment Using Deep Neural Networks. 488-502 - Eva Valterova, Franziska G. Rauscher, Radim Kolár:
Robust Automatic Montaging of Adaptive Optics Flood Illumination Retinal Images. 503-513
Radiomics, Predictive Models, and Quantitative Imaging
- Joshua Bridge, Simon P. Harding, Yalin Zheng:
End-to-End Deep Learning Vector Autoregressive Prognostic Models to Predict Disease Progression with Uneven Time Intervals. 517-531 - Roushanak Rahmat, David Harris-Birtill, David Finn, Yang Feng, Dean Montgomery, William H. Nailon, Stephen McLaughlin:
Radiomics-Led Monitoring of Non-small Cell Lung Cancer Patients During Radiotherapy. 532-546 - Declan Grant, Bartlomiej W. Papiez, Guy Parsons, Lionel Tarassenko, Adam Mahdi:
Deep Learning Classification of Cardiomegaly Using Combined Imaging and Non-imaging ICU Data. 547-558
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