default search action
Medical Image Analysis, Volume 57
Volume 57, October 2019
- Andrik Rampun, Karen López-Linares, Philip J. Morrow, Bryan W. Scotney, Hui Wang, Inmaculada Garcia Ocaña, Gregory Maclair, Reyer Zwiggelaar, Miguel Ángel González Ballester, Iván Macía:
Breast pectoral muscle segmentation in mammograms using a modified holistically-nested edge detection network. 1-17 - Ahmed Karam Eldaly, Yoann Altmann, Ahsan R. Akram, Paul McCool, Antonios Perperidis, Kevin Dhaliwal, Stephen McLaughlin:
Bayesian bacterial detection using irregularly sampled optical endomicroscopy images. 18-31 - Yunxiang Mao, Liang Han, Zhaozheng Yin:
Cell mitosis event analysis in phase contrast microscopy images using deep learning. 32-43 - Geng Chen, Bin Dong, Yong Zhang, Weili Lin, Dinggang Shen, Pew-Thian Yap:
XQ-SR: Joint x-q space super-resolution with application to infant diffusion MRI. 44-55 - Ullhas U. Hebbar, Rupak K. Banerjee:
Influence of coupled hemodynamics-arterial wall interaction on compliance in a realistic pulmonary artery with variable intravascular wall properties. 56-71 - Ilwoo Lyu, Hakmook Kang, Neil D. Woodward, Martin A. Styner, Bennett A. Landman:
Hierarchical spherical deformation for cortical surface registration. 72-88 - Baba C. Vemuri, Jiaqi Sun, Monami Banerjee, Zhixin Pan, Sara M. Turner, David D. Fuller, John R. Forder, Alireza Entezari:
A geometric framework for ensemble average propagator reconstruction from diffusion MRI. 89-105 - Christian Payer, Darko Stern, Marlies Feiner, Horst Bischof, Martin Urschler:
Segmenting and tracking cell instances with cosine embeddings and recurrent hourglass networks. 106-119 - Xiaofei Du, Maximilian Allan, Sebastian Bodenstedt, Lena Maier-Hein, Stefanie Speidel, Alessio Dore, Danail Stoyanov:
Patch-based adaptive weighting with segmentation and scale (PAWSS) for visual tracking in surgical video. 120-135 - Liang Wang, Patrick Clarysse, Zhengjun Liu, Bin Gao, Wanyu Liu, Pierre Croisille, Philippe Delachartre:
A gradient-based optical-flow cardiac motion estimation method for cine and tagged MR images. 136-148 - Guodong Zeng, Guoyan Zheng:
Holistic decomposition convolution for effective semantic segmentation of medical volume images. 149-164 - Yigal Shenkman, Bilal Qutteineh, Leo Joskowicz, Adi Szeskin, Yusef Azraq, Arnaldo Mayer, Iris Eshed:
Automatic detection and diagnosis of sacroiliitis in CT scans as incidental findings. 165-175 - Moran Rubin, Omer Stein, Nir A. Turko, Yoav Nygate, Darina Roitshtain, Lidor Karako, Itay Barnea, Raja Giryes, Natan T. Shaked:
TOP-GAN: Stain-free cancer cell classification using deep learning with a small training set. 176-185 - Davood Karimi, Qi Zeng, Prateek Mathur, Apeksha Avinash, Sara Mahdavi, Ingrid Spadinger, Purang Abolmaesumi, Septimiu E. Salcudean:
Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images. 186-196 - Angela W. C. Lee, Uyen Chau Nguyen, Orod Razeghi, Justin Gould, Baldeep Sidhu, Benjamin Sieniewicz, Jonathan M. Behar, M. Mafi-Rad, Gernot Plank, Frits W. Prinzen, C. Aldo Rinaldi, Kevin Vernooy, Steven A. Niederer:
A rule-based method for predicting the electrical activation of the heart with cardiac resynchronization therapy from non-invasive clinical data. 197-213 - Marie Piraud, Markus Wennmann, Laurent Kintzelé, Jens Hillengass, Ulrich Keller, Georg Langs, Marc-André Weber, Björn H. Menze:
Towards quantitative imaging biomarkers of tumor dissemination: A multi-scale parametric modeling of multiple myeloma. 214-225 - Adrian V. Dalca, Guha Balakrishnan, John V. Guttag, Mert R. Sabuncu:
Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces. 226-236 - Yutong Xie, Jianpeng Zhang, Yong Xia:
Semi-supervised adversarial model for benign-malignant lung nodule classification on chest CT. 237-248
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.