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Image Processing 2022: San Diego, CA, USA
- Olivier Colliot, Ivana Isgum, Bennett A. Landman, Murray H. Loew:
Medical Imaging 2022: Image Processing, San Diego, CA, USA, February 20-24, 2022 / Online, March 21-27, 2022. SPIE Proceedings 12032, SPIE 2022, ISBN 9781510649392
Spie Medical imaging Awards and Plenary + 50th Anniversary Panel
- Jennifer N. Avari Silva:
Emerging clinical applications of medical extended reality (MXR).
Image Acquisition, Reconstruction, and restoration
- Praitayini Kanakaraj, Colin B. Hansen, Francois Rheault, Leon Y. Cai, Karthik Ramadass, Baxter P. Rogers, Kurt G. Schilling, Bennett A. Landman:
Mapping the impact of non-linear gradient fields on diffusion MRI tensor estimation. - Yaoqi Tang, Yufan Li, Hongshan Liu, Jiaxuan Li, Peiyao Jin, Yu Gan, Yuye Ling, Yikai Su:
Multi-scale sparse representation-based shadow inpainting for retinal OCT images. - Fangxu Xing, Xiaofeng Liu, Timothy G. Reese, Maureen Stone, Van J. Wedeen, Jerry L. Prince, Georges El Fakhri, Jonghye Woo:
Measuring strain in diffusion-weighted data using tagged magnetic resonance imaging. - Dewei Hu, Yuankai K. Tao, Ipek Oguz:
Unsupervised denoising of retinal OCT with diffusion probabilistic model. - Darlan M. Nakamura de Araújo, Denis H. P. Salvadeo, Davi D. de Paula:
A benchmark of denoising digital breast tomosynthesis in projection domain: neural network-based and traditional methods.
Deep Learning
- Marius Schmidt-Mengin, Vito A. G. Ricigliano, Benedetta Bodini, Emanuele Morena, Annalisa Colombi, Maryem Hamzaoui, Arya Yazdan Panah, Bruno Stankoff, Olivier Colliot:
Axial multi-layer perceptron architecture for automatic segmentation of choroid plexus in multiple sclerosis. - Pieter Kronemeijer, Efstratios Gavves, Jan-Jakob Sonke, Jonas Teuwen:
Tumor tracking in 4D CT images for adaptive radiotherapy. - Yuhao Guo, Bin Cai, Pengpeng Liang, Kaifeng Wang, Zhiyong Sun, Chi Xiong, Bo Song, Chaoshi Niu, Erkang Cheng:
Efficient network with ghost tied block for heart segmentation. - Farzin Soleymani, Mohammad Eslami, Tobias Elze, Bernd Bischl, Mina Rezaei:
Deep variational clustering framework for self-labeling large-scale medical images. - Maksim Kholiavchenko, Ilya Pershin, Bulat Maksudov, Tamerlan Mustafaev, Yixuan Yuan, Bulat Ibragimov:
Gaze-based attention to improve the classification of lung diseases. - Ange Lou, Shuyue Guan, Hanseok Ko, Murray H. Loew:
CaraNet: context axial reverse attention network for segmentation of small medical objects.
Image Quality
- Lucas W. Remedios, Leon Y. Cai, Colin B. Hansen, Samuel W. Remedios, Bennett A. Landman:
Efficient quality control with mixed CT and CTA datasets. - Prerak Mody, Nicolas F. Chaves-de-Plaza, Klaus Hildebrandt, René van Egmond, Huib de Ridder, Marius Staring:
Comparing Bayesian models for organ contouring in head and neck radiotherapy. - Yi-Yu Chou, Samuel W. Remedios, John A. Butman, Dzung L. Pham:
Automatic classification of MRI contrasts using a deep Siamese network and one-shot learning. - Muhan Shao, Lianrui Zuo, Aaron Carass, Jiachen Zhuo, Rao P. Gullapalli, Jerry L. Prince:
Evaluating the impact of MR image harmonization on thalamus deep network segmentation. - Savannah Hays, Lianrui Zuo, Aaron Carass, Jerry L. Prince:
Evaluating the impact of MR image contrast on whole brain segmentation.
Monday morning Keynotes
- Piotr J. Slomka:
Explainable artificial-intelligence for diagnosis and risk estimation from cardiovascular images.
Classification and Detection
- Hellena Hempe, Eren Bora Yilmaz, Carsten Meyer, Mattias P. Heinrich:
Opportunistic CT screening for degenerative deformities and osteoporotic fractures with 3D DeepLab. - Bumjun Jung, Lin Gu, Tatsuya Harada:
Graph interaction for automated diagnosis of thoracic disease using x-ray images. - Mariana Vasquez, Suhev Shakya, Ian Wang, Jacob Furst, Roselyne Tchoua, Daniela Raicu:
Interactive deep learning for explainable retinal disease classification. - James D. Dormer, Michael Villordon, Maysam Shahedi, Ka'Toria N. Leitch, Quyen N. Do, Yin Xi, Matthew A. Lewis, Ananth J. Madhuranthakam, Christina L. Herrera, Catherine Y. Spong, Diane M. Twickler, Baowei Fei:
CascadeNet for hysterectomy prediction in pregnant women due to placenta accreta spectrum. - Moshe Raboh, Dana Levanony, Paul Dufort, Arkadiusz Sitek:
Context in medical imaging: the case of focal liver lesion classification. - Molly O'Brien, Julia V. Bukowski, Greg Hager, Aria Pezeshk, Mathias Unberath:
Evaluating neural network robustness for melanoma classification using mutual information.
Segmentation I
- Audrey Duran, Gaspard Dussert, Carole Lartizien:
Learning to segment prostate cancer by aggressiveness from scribbles in bi-parametric MRI. - Yida Chen, Xiaoyan Zhang, Christopher M. Haggerty, Joshua V. Stough:
Fully automated multi-heartbeat echocardiography video segmentation and motion tracking. - Martijn M. A. Bosma, Arkadiy Dushatskiy, Monika Grewal, Tanja Alderliesten, Peter A. N. Bosman:
Mixed-block neural architecture search for medical image segmentation. - Chen Shen, Holger R. Roth, Vishwesh Nath, Yuichiro Hayashi, Masahiro Oda, Kazunari Misawa, Kensaku Mori:
Effective hyperparameter optimization with proxy data for multi-organ segmentation. - Jie Qiu, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Nobuyoshi Takeshita, Masaaki Ito, Kensaku Mori:
Spatial label smoothing via aleatoric uncertainty for bleeding region segmentation from laparoscopic videos. - Fereshteh Yousefirizi, Natalia Dubljevic, Shadab Ahamed, Ingrid Bloise, Claire Gowdy, Joo Hyun O, Youssef Farag, Rodrigue de Schaetzen, Patrick Martineau, Don Wilson, Carlos F. Uribe, Arman Rahmim:
Convolutional neural network with a hybrid loss function for fully automated segmentation of lymphoma lesions in FDG PET images. - Hui Xie, Jui-Kai Wang, Randy H. Kardon, Mona Kathryn Garvin, Xiaodong Wu:
Automated macular OCT retinal surface segmentation in cases of severe glaucoma using deep learning.
Vascular imaging
- Zhangxing Bian, Jiayang Zhong, Yanglong Lu, Chuck R. Hatt, Nicholas S. Burris:
LitCall: learning implicit topology for CNN-based aortic landmark localization. - Dieuwertje Alblas, Christoph Brune, Jelmer M. Wolterink:
Deep-learning-based carotid artery vessel wall segmentation in black-blood MRI using anatomical priors.
Segmentation II
- Sean Mullan, Milan Sonka:
Visual attribution for deep learning segmentation in medical imaging. - Xiaofeng Liu, Chaehwa Yoo, Fangxu Xing, C.-C. Jay Kuo, Georges El Fakhri, Je-Won Kang, Jonghye Woo:
Unsupervised domain adaptation for segmentation with black-box source model. - Katharina Hoebel, Christopher P. Bridge, Andréanne Lemay, Ken Chang, Jay B. Patel, Bruce Rosen, Jayashree Kalpathy-Cramer:
Do I know this? segmentation uncertainty under domain shift.
Shape and Model-based Analysis
- Manon Ansart, Thierry Cresson, Benjamin Aubert, Jacques A. de Guise, Carlos Vázquez:
Statistical shape model of the spine fitting study: impact of clipping the latent representation. - Ashwin Kumar, Simon N. Vandekar, Kurt Schilling, Aashim Bhatia, Bennett A. Landman, Seth A. Smith:
Mapping pediatric spinal cord development with age. - Rueben A. Banalagay, Jack H. Noble:
Active shape models with locally weighted components. - Peiyu Duan, Shuo Han, Lianrui Zuo, Yang An, Yihao Liu, Ahmed Alshareef, Junghoon Lee, Aaron Carass, Susan M. Resnick, Jerry L. Prince:
Cranial meninges reconstruction based on convolutional networks and deformable models: applications to longitudinal study of normal aging. - Yang Zhao, Ke Lu, Jian Xue, Bin Huang, Haiyi Wang, Huan Wu, Yifei Wang:
SCU-Net: shape constraint U-Net for prostate segmentation in MR images. - Iris N. Vos, Ynte M. Ruigrok, Kimberley M. Timmins, Birgitta K. Velthuis, Hugo J. Kuijf:
Improving automated intracranial artery labeling using atlas-based features in graph convolutional nets.
Registration
- Monty Santarossa, Ayse Kilic, Claus von der Burchard, Lars Schmarje, Claudius Zelenka, Stefan Reinhold, Reinhard Koch, Johann Roider:
MedRegNet: unsupervised multimodal retinal-image registration with GANs and ranking loss. - Konstantinos Ntatsis, Luisa Sánchez Brea, Danilo Andrade De Jesus, João Barbosa Breda, Theo van Walsum, Edwin Bennink, Stefan Klein:
Motion correction in retinal optical coherence tomography imaging using deep learning registration. - Sven Krönke, Jens von Berg, Matthias Brück, Daniel Bystrov, André Gooßen, Tim Harder, Bernd Lundt, Jan Marek May, Nataly Wieberneit, Tobias Wissel, Omar Hertgers, Hildo J. Lamb, Stewart Young:
CNN-based pose estimation for assessing quality of ankle-joint X-ray images. - Wenzhe Yin, Vadim O. Chagin, M. Cristina Cardoso, Karl Rohr:
Non-rigid registration of temporal live cell microscopy image sequences using deep learning. - Rahul Hingorani, Nicole L. Brown, Christopher M. Cervantes, Robert H. Brown, Andrew S. Gearhart:
On characterizing the sensitivity of lung computed tomography biomarkers to registration error.
Brain imaging and Disorders
- Hao Li, Qibang Zhu, Dewei Hu, Manasvi R. Gunnala, Hans J. Johnson, Omar Sherbini, Francesco Gavazzi, Russell D'Aiello, Adeline Vanderver, Jeffrey D. Long, Jane S. Paulsen, Ipek Oguz:
Human brain extraction with deep learning. - Virgilio Kmetzsch, Emmanuelle Becker, Dario Saracino, Vincent Anquetil, Daisy Rinaldi, Agnès Camuzat, Thomas Gareau, Isabelle Le Ber, Olivier Colliot:
A multimodal variational autoencoder for estimating progression scores from imaging and microRNA data in rare neurodegenerative diseases. - Yeun Kim, Evelyn Malamut, Cassandra E. Meyer, Allan MacKenzie-Graham, David W. Shattuck:
Mouse brain extraction using 2-Stage CNNs. - Karthik Ramadass, Francois Rheault, Leon Y. Cai, Lucas W. Remedios, Micah D'Archangel, Ilwoo Lyu, Laura A. Barquero, Allen T. Newton, Laurie E. Cutting, Yuankai Huo, Bennett A. Landman:
Ultra-high-resolution mapping of cortical layers 3T-guided 7T MRI. - Leon Y. Cai, Francois Rheault, Cailey I. Kerley, Katherine S. Aboud, Lori L. Beason-Held, Andrea T. Shafer, Susan M. Resnick, Lori C. Jordan, Adam W. Anderson, Kurt G. Schilling, Bennett A. Landman:
Joint independent component analysis for hypothesizing spatiotemporal relationships between longitudinal gray and white matter changes in preclinical Alzheimer's disease.
Image Processing and imaging Informatics: Joint Session with Conferences 12032 and 12037
- Masaki Ikuta, Jun Zhang:
A deep recurrent neural network with primal-dual optimization for CT metal artifact reduction. - Siqi Li, Guobao Wang:
A deep kernel method for PET image reconstruction.
Quantitative Image Analysis
- Qi Yang, Xin Yu, Ho Hin Lee, Yucheng Tang, Shunxing Bao, Kristofer S. Gravenstein, Ann Zenobia Moore, Sokratis Makrogiannis, Luigi Ferrucci, Bennett A. Landman:
Quantification of muscle, bones, and fat on single slice thigh CT. - Kaiwen Xu, Riqiang Gao, Yucheng Tang, Steve A. Deppen, Kim L. Sandler, Michael N. Kammer, Sanja L. Antic, Fabien Maldonado, Yuankai Huo, Mirza S. Khan, Bennett A. Landman:
Extending the value of routine lung screening CT with quantitative body composition assessment. - Xiaofeng Liu, Fangxu Xing, Thibault Marin, Georges El Fakhri, Jonghye Woo:
Variational inference for quantifying inter-observer variability in segmentation of anatomical structures. - Gasper Podobnik, Primoz Strojan, Primoz Peterlin, Bulat Ibragimov, Tomaz Vrtovec:
Parotid gland segmentation with nnU-Net: deployment scenario and inter-observer variability analysis.
Generative Models
- Zong Fan, Varun A. Kelkar, Mark A. Anastasio, Hua Li:
Application of DatasetGAN in medical imaging: preliminary studies. - Robert V. Bergen, Jean-François Rajotte, Fereshteh Yousefirizi, Ivan S. Klyuzhin, Arman Rahmim, Raymond T. Ng:
3D PET image generation with tumour masks using TGAN. - Xiaofeng Liu, Fangxu Xing, Jerry L. Prince, Maureen Stone, Georges El Fakhri, Jonghye Woo:
Structure-aware unsupervised tagged-to-cine MRI synthesis with self disentanglement. - Zhiwei Zhai, Yining Wang, Bob D. de Vos, Julia M. H. Noothout, Nils Planken, Ivana Isgum:
Generative adversarial network for coronary artery plaque synthesis in coronary CT angiography. - Chih-Wei Chang, Yang Lei, Tonghe Wang, Jun Zhou, Liyong Lin, Jeffrey D. Bradley, Tian Liu, Xiaofeng Yang:
A deep learning approach to transform two orthogonal X-ray images to volumetric images for image-guided proton therapy. - Tong Zheng, Hirohisa Oda, Yuichiro Hayashi, Shota Nakamura, Masaki Mori, Hirotsugu Takabatake, Hiroshi Natori, Masahiro Oda, Kensaku Mori:
Coarse-to-fine cascade framework for cross-modality super-resolution on clinical/micro CT dataset.
Poster Session
- Yuzhe Wang, Francois Rheault, Kurt G. Schilling, Lori L. Beason-Held, Andrea T. Shafer, Susan M. Resnick, Bennett A. Landman:
Longitudinal changes of connectomes and graph theory measures in aging. - Anurag Vaidya, Joshua V. Stough, Aalpen A. Patel:
Perceptually improved T1-T2 MRI translations using conditional generative adversarial networks. - Rahul Mishra, Krishan Sharma, Arnav Bhavsar:
Reconstruction of visual stimulus from the EEG recordings via generative adversarial network. - Rucha Deshpande, Mark A. Anastasio, Frank J. Brooks:
Evaluating the capacity of deep generative models to reproduce measurable high-order spatial arrangements in diagnostic images. - Djennifer K. Madzia-Madzou, Hugo J. Kuijf:
Progressive GANomaly: anomaly detection with progressively growing GANs. - Stien Van Steen, Dimitar Petrov, Rik Godon, Stijn Bonte, Hilde Bosmans:
Image quality assessment of chest CT scans used in functional respiratory imaging. - Qian Wang, Huiqiao Xie, Tonghe Wang, Justin Roper, Xiangyang Tang, Jeffrey D. Bradley, Tian Liu, Xiaofeng Yang:
Iterative material decomposition with gradient L0-norm minimization for dual-energy CT. - Chelsea A. S. Dunning, Kishore Rajendran, Joel G. Fletcher, Cynthia H. McCollough, Shuai Leng:
Impact of improved spatial resolution on radiomic features using photon-counting-detector CT. - Huijuan Zhang, Wei Bo, Depeng Wang, Anthony DiSpirito III, Chuqin Huang, Nikhila Nyayapathi, Emily Zheng, Tri Vu, Yiyang Gong, Junjie Yao, Wenyao Xu, Jun Xia:
Deep-e: a fully-dense neural network for improving the elevation resolution in linear-array-based photoacoustic tomography. - Minwoo Yu, Minah Han, Jongduk Baek:
A convolutional neural network based super resolution technique of CT image utilizing both sinogram domain and image domain data. - Mikhail Mikerov, Koen Michielsen, Nikita Moriakov, Ioannis Sechopoulos:
Adding patient motion from DCE-MRI to anthropomorphic phantoms for dedicated breast CT. - Serena Z. Shi, Nadav Shapira, Peter B. Noël, Sebastian Meyer:
Displacement retrieval for speckle-based X-ray phase-contrast imaging using a convolutional neural network. - Simona Bottani, Elina Thibeau-Sutre, Aurélien Maire, Sebastian Ströer, Didier Dormont, Olivier Colliot, Ninon Burgos:
Homogenization of brain MRI from a clinical data warehouse using contrast-enhanced to non-contrast-enhanced image translation with U-Net derived models. - Tiange Liu, Meng Tan, Yubing Tong, Drew A. Torigian, Jayaram K. Udupa:
An anatomy-based iteratively searching convolutional neural network for organ localization in CT images. - Chao Jin, Jayaram K. Udupa, Liming Zhao, Yubing Tong, Dewey Odhner, Gargi Pednekar, Sanghita Nag, Sharon Lewis, Nicholas Poole, Sutirth Mannikeri, Sudarshana Govindasamy, Aarushi Singh, Joe Camaratta, Steve Owens, Drew A. Torigian:
Anatomy-guided deep learning for object localization in medical images. - Michal Brzus, Alexander B. Powers, Kevin Knoernschild, Jessica C. Sieren, Hans J. Johnson:
Multi-agent reinforcement learning pipeline for anatomical landmark detection in minipigs. - Ting Wang, Weifang Zhu, Meng Wang, Lianyu Wang, Zhongyue Chen, Tian Lin, Haoyu Chen, Xinjian Chen:
Multi-view-based automatic method for multiple diseases screening in retinal OCT images. - Mahdieh Shabanian, Abdullah-Al-Zubaer Imran, Adeel Siddiqui, Robert L. Davis, John J. Bissler:
3D deep neural network to automatically identify TSC structural brain pathology based on MRI. - Chao Guo, Weifang Zhu, Ting Wang, Tian Lin, Haoyu Chen, Xinjian Chen:
Retinal OCT image report generation based on visual and semantic topic attention model. - Mahdieh Shabanian, Markus T. Wenzel, John P. DeVincenzo:
Infant brain age classification: 2D CNN outperforms 3D CNN in small dataset. - Weize Liu, Yaping Wang, Youze He, Jingsong Wu, Xiujuan Geng:
Structural connectivity-based subtyping of healthy individuals using elastic net subspace clustering. - Holger Kunze, Florian Kordon, Andreas Maier, Katharina Breininger:
Direct and indirect image rotation estimation methods of orthopedic x-ray images. - Celia Martín Vicario, Florian Kordon, Felix Denzinger, Jan Siad El Barbari, Maxim Privalov, Jochen Franke, Andreas Maier, Holger Kunze:
Normalization techniques for CNN based analysis of surgical cone beam CT volumes. - Colin J. Gibbons, Jon D. Klingensmith:
MRI-derived cardiac fat modelling for use in ultrasound tissue labelling and classification. - Arash Javanmardi, Mahdi Hosseinzadeh, Ghasem Hajianfar, Amir Hossein Nabizadeh, Seyed Masoud Rezaeijo, Arman Rahmim, Mohammad R. Salmanpour:
Multi-modality fusion coupled with deep learning for improved outcome prediction in head and neck cancer. - Jiaming Li, Toshiyuki Adachi, Saori Takeyama, Masahiro Yamaguchi, Yukako Yagi:
U-Net based mitosis detection from H&E-stained images with the semi-automatic annotation using pHH3 IHC-stained images. - Hunter Morera, Palak Dave, Yaroslav Kolinko, Kurtis Allen, Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
Classification of global microglia proliferation based on deep learning with local images. - Hana Mertanová, Jan Kybic, Jarmila Stanková, Petr Dzubák, Marián Hajdúch:
Learning to segment cell nuclei in phase-contrast microscopy from fluorescence images for drug discovery. - Quan Liu, Bryan A. Millis, Zuhayr Asad, Can Cui, William F. Dean, Isabelle T. Smith, Christopher Madden, Joseph T. Roland, Jeffrey P. Zwerner, Shilin Zhao, Lee E. Wheless, Yuankai Huo:
Integrate memory efficiency methods for self-supervised learning on pathological image analysis. - Bohao Chen, Tong Xin, Hua Han, Xi Chen:
Performance analysis in serial-section electron microscopy image registration of neuronal tissue. - Miguel Plazas, Raúl Ramos-Pollán, Fabian León, Fabio Martínez:
Towards reduction of expert bias on Gleason score classification via a semi-supervised deep learning strategy. - Maryam Sadeghi, Pedro Neto, Arnau Ramos-Prats, Federico Castaldi, Enrica Paradiso, Naghmeh Mahmoodian, Francesco Ferraguti, Georg Göbel:
Automatic 2D to 3D localization of histological mouse brain sections in the reference atlas using deep learning. - William J. Herrera, Simone Appenzeller, Fabiano Reis, Danilo Pereira, Mariana P. Bento, Letícia Rittner:
Automated quality check of corpus callosum segmentation using deep learning. - Samuel Joutard, Reuben Dorent, Tom Vercauteren, Marc Modat:
A Pareto front based methodology to better assess medical image registration algorithms. - Ho Hin Lee, Yucheng Tang, Shunxing Bao, Yan Xu, Qi Yang, Xin Yu, Agnes B. Fogo, Raymond Harris, Mark P. de Caestecker, Jeffrey M. Spraggins, Mattias P. Heinrich, Yuankai Huo, Bennett A. Landman:
Supervised deep generation of high-resolution arterial phase computed tomography kidney substructure atlas. - Georgios Andreadis, Peter A. N. Bosman, Tanja Alderliesten:
Multi-objective dual simplex-mesh based deformable image registration for 3D medical images - proof of concept. - Pranjal Sahu, Samuel Gerber, Qingyu Zhao, Tung Nguyen, Matt McCormick, Beatriz Paniagua, Jared Vicory:
Thin shell demons for dental scan registration. - Arkadiy Dushatskiy, Gerry Lowe, Peter A. N. Bosman, Tanja Alderliesten:
Data variation-aware medical image segmentation. - Ammar Alsheghri, Farnoosh Ghadiri, Ying Zhang, Olivier Lessard, Julia Keren, Farida Cheriet, François Guibault:
Semi-supervised segmentation of tooth from 3D scanned dental arches. - Ziga Bizjak, Aichi Chien, Iza Burnik, Ziga Spiclin:
Novel dataset and evaluation of state-of-the-art vessel segmentation methods. - Xiaodan Xing, Yinzhe Wu, David N. Firmin, Peter Gatehouse, Guang Yang:
Synthetic velocity mapping cardiac MRI coupled with automated left ventricle segmentation. - Jared Vicory, Pranjal Sahu, Hwabok Wee, Hannah Nam, Avani Chopra, Spence Reid, Gregory S. Lewis, Sreekanth Arikatla:
Automated fractured femur segmentation using CNN. - Zihuan Qiu, Zhichuan Wang, Miaomiao Zhang, Ziyong Xu, Jie Fan, Linfeng Xu:
BDG-Net: boundary distribution guided network for accurate polyp segmentation. - Christian N. Kruse, Mattias P. Heinrich:
Bridging the domain gap for medical image segmentation with multimodal MIND features. - Tudor Dascalu, Artem Kuznetsov, Bulat Ibragimov:
Benefits of auxiliary information in deep learning-based teeth segmentation. - Ilkin Isler, Curtis Lisle, Justin Rineer, Patrick Kelly, Damla Turgut, Jacob Ricci, Ulas Bagci:
Enhancing organ at risk segmentation with improved deep neural networks. - Sokratis Makrogiannis, Nagasoujanya Annasamudram, Taposh Biswas:
TIDAQUNET: tissue identification and quantification network for mid-thigh CT segmentation. - Jia Jia, Yaping Wang, Chenyu Yan:
BAA-Net: attention-based CNN for automatic placental segmentation of MR images. - Sarah D. Verboom, Marco Caballo, Mireille J. M. Broeders, Jonas Teuwen, Ioannis Sechopoulos:
Deep learning-based breast tissue segmentation in digital mammography: generalization across views and vendors. - Zicong Zhou, Guojun Liao:
A novel approach to form normal distribution of medical image segmentation based on multiple doctors' annotations. - Nam H. Le, Edgar A. Samaniego, Ashrita Raghuram, Sebastián Sánchez, Honghai Zhang, Milan Sonka:
Semi-automated intracranial aneurysm segmentation and neck detection. - Clara Dacho, David Gabauer, David Brunner, Lukas Fischer:
2D nnUNet for classification and segmentation of anatomical structures in fetal torso ultrasound. - Konrad Pieszko, Aakash D. Shanbhag, Aditya Killekar, Mark Lemley, Yuka Otaki, Serge D. Van Kriekinge, Paul Kavanagh, Robert J. H. Miller, Edward J. Miller, Timothy M. Bateman, Damini Dey, Daniel S. Berman, Piotr J. Slomka:
Calcium scoring in low-dose ungated chest CT scans using convolutional long-short term memory networks. - Moshe Yerachmiel, Hayit Greenspan:
Weakly supervised brain tumor segmentation via semantic affinity deep neural network. - Pengfei Fu, Yaping Wang, Jinyuan Shen, Xiujuan Geng:
Investigation of multi-cohort brain MRI segmentation in infants. - Felix Thielke, Farina Kock, Annika Hänsch, Joachim Georgii, Nasreddin Abolmaali, Itaru Endo, Hans Meine, Andrea Schenk:
Improving deep learning based liver vessel segmentation using automated connectivity analysis. - Xin Yu, Yucheng Tang, Qi Yang, Ho Hin Lee, Shunxing Bao, Ann Zenobia Moore, Luigi Ferrucci, Bennett A. Landman:
Accelerating 2D abdominal organ segmentation with active learning. - Zachary A. Stoebner, Daiwei Lu, Seok Hee Hong, Nicholas L. Kavoussi, Ipek Oguz:
Segmentation of kidney stones in endoscopic video feeds. - Jasper W. van der Graaf, Miranda L. van Hooff, Constantinus F. M. Buckens, Nikolas Lessmann:
Segmentation of vertebrae and intervertebral discs in lumbar spine MR images with iterative instance segmentation. - Yang Lei, Zhen Tian, Richard L. J. Qiu, Tonghe Wang, Justin Roper, Kristin Higgins, Jeffrey D. Bradley, Tian Liu, Xiaofeng Yang:
Deep-learning-based markerless tumor localization using 2D KV/MV image. - Tao Hu, Hayato Itoh, Masahiro Oda, Shinji Saiki, Nobutaka Hattori, Koji Kamagata, Shigeki Aoki, Kensaku Mori:
Size-reweighted cascaded fully convolutional network for substantia nigra segmentation from T2 MRI. - Helena R. Torres, Bruno Oliveira, Pedro Morais, Anne Fritze, Cahit Birdir, Mario Rüdiger, Jaime C. Fonseca, João L. Vilaça:
Fetal head circumference delineation using convolutional neural networks with registration-based ellipse fitting. - Shadab Ahamed, Natalia Dubljevic, Ingrid Bloise, Claire Gowdy, Patrick Martineau, Don Wilson, Carlos F. Uribe, Arman Rahmim, Fereshteh Yousefirizi:
A cascaded deep network for automated tumor detection and segmentation in clinical PET imaging of diffuse large B-cell lymphoma. - Cam Nguyen, Zuhayr Asad, Ruining Deng, Yuankai Huo:
Evaluating transformer-based semantic segmentation networks for pathological image segmentation. - Lipeng Xie, Jayaram K. Udupa, Yubing Tong, Joseph M. McDonough, Caiyun Wu, Carina Lott, Jason B. Anari, Patrick J. Cahill, Drew A. Torigian:
Automatic lung segmentation in dynamic thoracic MRI using two-stage deep convolutional neural networks. - Aditya Killekar, Kajetan Grodecki, Andrew Lin, Sebastien Cadet, Priscilla McElhinney, Aryabod Razipour, Cato Chan, Barry D. Pressman, Peter Julien, Peter Chen, Judit Simon, Nitesh Nerlekar, Pál Maurovich-Horvat, Nicola Gaibazzi, Udit Thakur, Elisabetta Mancini, Cecilia Agalbato, Jiro Munechika, Hidenari Matsumoto, Roberto Menè, Damini Dey, Gianfranco Parati, Franco Cernigliaro, Camilla Torlasco, Gianluca Pontone, Piotr J. Slomka:
COVID-19 lesion segmentation using convolutional LSTM for self-attention. - Chihiro Hattori, Daisuke Furukawa, Fukashi Yamazaki, Yasuko Fujisawa, Takuya Sakaguchi:
Centerline detection and estimation of pancreatic duct from abdominal CT images. - Maria G. Baldeon Calisto, Susana K. Lai-Yuen:
C-MADA: unsupervised cross-modality adversarial domain adaptation framework for medical image segmentation. - Libin Liang, Tingting Gao, Hui Ding, Guangzhi Wang:
A distribution-based method for thermal damage model analysis and optimization in brain laser interstitial thermal therapy. - Hayato Itoh, Masahiro Oda, Shinji Saiki, Nobutaka Hattori, Koji Kamagata, Shigeki Aoki, Kensaku Mori:
Substantia nigra analysis by tensor decomposition of T2-weighted images for Parkinson's disease diagnosis. - Leon Y. Cai, Costin Tanase, Adam W. Anderson, Karthik Ramadass, Francois Rheault, Chelsea A. Lee, Niral J. Patel, Sky Jones, Lauren M. LeStourgeon, Alix Mahon, Sumit Pruthi, Kriti Gwal, Arzu Ozturk, Hakmook Kang, Nicole Glaser, Simona Ghetti, Sarah S. Jaser, Lori C. Jordan, Bennett A. Landman:
Multimodal neuroimaging in pediatric type 1 diabetes: a pilot multisite feasibility study of acquisition quality, motion, and variability. - Chao Guo, Weifang Zhu, Meng Wang, Ming Liu, Zhongyue Chen, Xinjian Chen:
Acute branch retinal artery occlusion segmentation based on Bayes posterior probability and deep learning. - Chenyu Gao, Linghao Jin, Jerry L. Prince, Aaron Carass:
Effects of defacing whole head MRI on neuroanalysis.
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