MICAD2021 The 2nd International Conference on Medical Imaging and Computer-Aided Diagnosis March 25-26, 2021 | Webiner Welcome Messages Dear colleagues, It is our great pleasure and privilege to welcome you to the virtual edition of MICAD2021, the 2nd International Conference on Medical Imaging and Computer-Aided Diagnosis. The conference will be held from March 25th to 26th, 2021 and is now accessible to registered participants worldwide. The annual MICAD conference attracts world leading biomedical scientists, engineers, and clinicians from a wide range of disciplines associated with medical imaging and computer assisted diagnosis. Submitted papers will be peer reviewed by conference committees, the accepted papers that presented at the conference will be included into MICAD2021 conference proceedings, and be published with Springer LNEE. The program will features 4 focused oral sessions, with speakers providing perspectives on related fields, both academic and commercial. We would like to thank and welcome everyone, and hope you will enjoy MICAD2021. Supporting Academic Organizations Media Partners Content Committee ...................................................................................................................................................................... 3 Time Schedule (London Time, GMT+0) ............................................................................................................... 5 Keynote Speakers (Ordered by Last Name)....................................................................................................... 8 Abstracts (in chronological order) ...................................................................................................................... 14 Keynote Session 1 ................................................................................................................................................ 14 Keynote Session 2 ................................................................................................................................................ 15 Oral Session 1: Computer-Aided Detection/Diagnosis......................................................................... 16 Oral Session 2: Automated Medical Image Analysis .............................................................................. 18 Oral Session 3: Medical Image Segmentation, Registration and Reconstruction ...................... 20 Oral Session 4: Machine learning and Deep learning ........................................................................... 22 Keynote Session 3 ................................................................................................................................................ 25 Keynote Session 4 ................................................................................................................................................ 26 Committee Conference Chair Dr. Ruidan Su, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China General Co-chair Prof. Yu-dong Zhang, University of Leicester, UK Program Chairs Prof. Alejandro F Frangi, University of Leeds, UK Prof. Joseph M. Reinhardt, The University of Iowa, IA, USA Dr. Han Liu, Shenzhen University, China Prof. Ryuji Hamamoto, Representative Director, Japanese Association for Medical Artificial Intelligence (JMAI), Japan Technical Program Committee Prof. Zakaria Belhachmi, Université Haute-Alsace, France Prof. Qiang (Shawn) Cheng, University of Kentucky, USA Prof. Sourav Dhar, Sikkim Manipal University, India Dr. Jan Ehrhardt, Institute for Medical Informatics, University of Lübeck, Germany Prof. Smain FEMMAM, IEEE senior member, University of Haute-Alsace France, France Dr. Linlin Gao, Ningbo University, China Dr. Maroun Geryes, Lebanese University, Lebanon Prof. Yuzhu Guo, Beihang University, China Prof. Zhiwei Huang, National University of Singapore, Singapore Dr. Yuankai Huo, Vanderbilt University, USA Dr. Sujatha Krishnamoorthy, Wenzhou Kean University, China Dr. Yuan Liang, University of California, Los Angeles, USA Dr. Cheng Lu, Case Western Reserve University, USA Dr. Na Ma, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China Dr. Mahsa Mohaghegh, Auckland University of Technology, New Zealand Prof. Xiang Pan, Jiangnan University, China Dr. Luca Parisi, Coventry University, UK Dr. Sivarama Krishnan Rajaraman, Lister Hill National Center for Biomedical Communications (LHNCBC), National Library of Medicine (NLM), National Institutes of Health (NIH), India Prof. Su RUAN, LITIS laboratory, University of Rouen, France Dr. Francesco Rundo, STMicroelectronics s.r.l., Catania, Italy Dr. Rachel Sparks, King’s College London, UK Dr. Vinesh Sukumar, University of Idaho, United States Dr. Gunasekar Thangarasu, Linton University College, Malaysia Dr. Gennaro Vessio, University of Bari, Italy Dr. Jichuan Xiong, Nanjing University of Science and Technology, China Dr. Lequan Yu, Stanford University, USA Dr. Yitian Zhao, iMED China group at Cixi Institute of Biomedical Engineering, Ningbo Institute of Industrial Technology, Chinese Academy of Sciences, China Dr. Yuyao Zhang, ShanghaiTech University, China Dr. Jun Zhuang, Indiana University-Purdue University at Indianapolis (IUPUI), USA Time Schedule (London Time, GMT+0) March 25th 07:55-08:00 Opening Speech 08:00-11:30 Keynote Session Chair: Prof. Alejandro F Frangi From medical image computing to In silico trials of medical devices 08:00-08:30 Prof. Alejandro F Frangi | University of Leeds, UK Accelerating Deep Learning Medical Image Analysis in Radiology 08:30-09:00 Prof. Leo Joskowicz | The Hebrew University of Jerusalem, Israel Artificial Intelligence in Bioimage Analysis 09:00-09:30 Prof. Erik Meijering | University of New South Wales, Australia Chair: Prof. Yudong Zhang Large cohort analysis in medical image processing 09:30-10:00 Prof. Robin Strand | Uppsala University, Sweden Safe instrument detection during surgery 10:00-10:30 Prof. Raphael Sznitman | University of Bern, Switzerland Deep Learning Solutions for Real World Healthcare Applications 10:30-11:00 Dr. Ayelet Akselrod-Ballin | Zebra Medical Vision Ltd, Israel Oral Session 1 11:00-12:00 Computer-Aided Detection/Diagnosis Chair: Promoting Cardiovascular Health Using a Recommendation System Paper ID: 7 Orlando Belo | University of Minho, Portugal Information Technologies in Complex Reconstructive Maxillofacial Surgery 11 Mikhail Mikhailovich Novikov | Institute on Laser and Information Technologies of RAS, Russia Machine Learning-based Imaging in Connected Vehicles Environment 16 Sayon Karmakar | University of Arkansas at Little Rock, USA Predicting Neurostimulation Responsiveness with Dynamic Brain Network Measures 43 Jinwei Lang | Hefei Institutes of Physical Science, Chinese Academy of Sciences, China Data augmentation for breast cancer mass segmentation 46 Jailin Clément | GE Healthcare, France 12:00-12:30 Break Oral Session 2 12:30-13:30 Automated Medical Image Analysis Chair: Asmaa Haja Unsharp Masking with Local Adaptive Contrast Enhancement of Paper ID: 14 Medical Images Ivo Draganov | Technical University of Sofia, Bulgaria A fully automated end-to-end process for fluorescence microscopy images of yeast cells: From segmentation to detection and 27 classification Asmaa Haja | University of Groningen, Netherlands Quantification of Epicardial Adipose Tissue in Low-Dose Computed 51 Tomography Images Goncharov Mikhail | Skolkovo Institute of Science and Technology, Russia A new content based image retrieval system for SARS-CoV-2 33 computer-aided diagnosis Marcelo Mendoza | Universidad Técnica Federico Santa María, Chile Geometrically Matched Multi-source Microscopic Image Synthesis 40 Using Bidirectional Adversarial Networks Dali Wang | Univeristy of Tennessee, USA Covid-19 Chest CT Scan Image Classification Using LCKSVD and 20 Frozen Sparse Coding Kaveen Liyanage | Montana State University, USA March 26th Oral Session 3 07:00-08:00 Medical Image Segmentation, Registration and Reconstruction Chair: Nachwa Aboubakr The Art-of-Hyper-Parameter Optimization with Desirable Feature Paper ID: 36 Selection Priynka Sharma | University of the South Pacific, Fiji A Dual supervision guided attentional network for multimodal MR 4 brain tumor segmentation Tongxue Zhou | Université de Rouen Normastic, France Three-dimensional image reconstruction of murine heart using image 10 processing Haowei Zhong | South China Agricultural University, China Glioblastoma Multiforme Patient Survival Prediction 34 Snehal Rajput RamAchal Singh | Pandit Deendayal Petroleum University, India Color-based Fusion of MRI Modalities for Brain Tumor Segmentation 50 Nachwa Aboubakr | University Grenoble Alpes, France Oral Session 4 08:00-10:00 Machine learning and Deep learning Chair: Dimitris Glotsos 2Be3-Net: Combining 2D and 3D convolutional neural networks for Paper ID: 12 3D PET scans predictions Ronan Thomas | EURA NOVA FRANCE, France A Hybrid Deep Model for Brain Tumor Classification 21 Hamail Ayaz | Institue of Technology Sligo, Ireland A Systematic Literature Review of Machine Learning Applications for 28 Community-Acquired Pneumonia Daniel Lozano-Rojas | University of Leicester, UK Photograph to X-ray image translation for anatomical mouse 31 mapping in preclinical nuclear molecular imaging Dimitris Glotsos | University of West Attica, Greece Active strain-statistical models for reconstructing multidimensional 32 images of lung tissue lesions Ekaterina Guryanova | Russian