Location: Vancouver Convention Centre [East Building Level 1], Meeting room *6*
(virtual attendance is available on the MICCAI virtual platform, registration is needed)
8:00-8:05 Welcome
8:05-8:45 Keynote MTSAIL
8:45-10:00 Oral Session 1 MTSAIL
10:00 -10:15 Coffee Break
10:15-11:15 Oral Session 2 LEAF
11:15-12:00 Keynote LEAF
12:00-12:30 Introduction to Universal Lesion Segmentation Challenge and Open Discussion
All times are in PDT (UTC-7) Vancouver, British Columbia, Canada.
For the optional poster presentation: The maximum poster size for MICCAI 2023 is A0, (i.e. 841 x 1189 mm or 33.1 x 46.8 in) (Width x Height) portrait format. Poster Hall for the workshops will be at Ground Level Exhibition B-C where the coffee break and lunches will be served. There will be labels on the poster board with the acronyms of each Satellite Event.
Accepted submissions to the MTSAIL&LEAF 2023 have been published as Springer Lecture Notes in Computer Science (LNCS) series.
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops
https://link.springer.com/book/9783031474248
Participants may attend the workshop virtually but are encouraged to join in-person.
Accepted submissions to the MTSAIL workshop:
[8:45-9:00] Learning Dynamic MRI Reconstruction with Convolutional Network Assisted Reconstruction Swin Transformer
Di Xu (University of California, Los Angeles)*; Hengjie Liu (University of California, Los Angeles); Dan Ruan (University of California, Los Angeles); Ke Sheng (University of California, San Francisco)
https://arxiv.org/abs/2309.10227
[9:00-9:15] A Groupwise Method for the Reconstruction of Hypergraph Representation of Resting-State Functional Networks
Mingyang Xia (University of southern california)*; Yonggang Shi (University of Southern California)
[9:15-9:30] MomentaMorph: Unsupervised Spatial-Temporal Registration with Momenta, Shooting and Correction
Zhangxing Bian (Johns Hopkins University)*; Shuwen Wei (Johns Hopkins University); Yihao Liu (Johns Hopkins University); Junyu Chen (Johns Hopkins University); Jiachen Zhuo (University of Maryland); Fangxu Xing (Massachusetts General Hospital / Harvard Medical School); Jonghye Woo (Massachusetts General Hospital / Harvard Medical School); Aaron Carass (Johns Hopkins University, USA); Jerry L Prince (Johns Hopkins University)
https://arxiv.org/abs/2308.02949
[9:30-9:45] FusionNet: a frame interpolation network for 4D heart models
Chujie Chang (Kyushu University); Shoko Miyauchi (Kyushu University)*; Ken'ichi Morooka (Kumamoto University); Ryo Kurazume (Kyushu University); Oscar Martinez Mozos (Örebro University)
[9:45-10:00] A New Large-Scale Video Dataset of the Eyelid Opening Degree for Deep Regression-based PERCLOS Estimation
Ko Taniguchi (University of Tsukuba)*; Takahiro Noguchi ( University of Tsukuba); Satoshi Iizuka (University of Tsukuba); Hiroyasu Ando (University of Tsukuba); Takashi Abe (University of Tsukuba); Kazuhiro Fukui (University of Tsukuba)
Accepted submissions to the LEAF workshop:
A Hierarchical Descriptor Framework for On-the-Fly Anatomical Location Matching between Longitudinal Studies
Halid Ziya Yerebakan (Siemens Healthineers)*; Gerardo Hermosillo (Siemens Medical Solutions, US); Yoshihisa Shinagawa (Siemens Healthineers); Simon Allen-Raffl (Siemens Healthineers); Mahesh Ranganath (Siemens Healthineers)
https://export.arxiv.org/abs/2308.07337
A Two-Species Model for Abnormal Tau Dynamics in Alzheimer's Disease
Zheyu Wen (UT Austin)*; Ali Ghafouri (UT Austin); George Biros (UT Austin)
Outlier Robust Disease Classification via Stochastic Confidence Network
Kyungsu Lee (DGIST)*; Haeyun Lee (SAMSUNG SDI); El Fakhri Georges (MGH); Jorge Sepulcre (Massachusetts General Hospital); Xiaofeng Liu (Harvard Medical School and MGH); Fangxu Xing (Massachusetts General Hospital / Harvard Medical School); Jonghye Woo (Massachusetts General Hospital / Harvard Medical School); Jae Youn Hwang (DGIST)
Efficient registration of longitudinal studies for follow-up lesion assessment by exploiting redundancy and composition of deformations
Sven Kuckertz (Fraunhofer Institute for Digital Medicine MEVIS)*; Stefan Heldmann (Fraunhofer MEVIS); Jan H. Moltz (Fraunhofer Institute for Digital Medicine MEVIS)