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ORCID15th ISBI 2018: Washington, DC, USA
- 15th IEEE International Symposium on Biomedical Imaging, ISBI 2018, Washington, DC, USA, April 4-7, 2018. IEEE 2018, ISBN 978-1-5386-3636-7
- Shu Zhang, Tuo Zhang, Xiao Li, Lei Guo, Tianming Liu:
Joint representation of cortical folding, structural connectivity and functional networks. 1-5 - Jingwen Yan, Kefei Liu, Huang Lv, Enrico Amico
, Shannon L. Risacher, Yu-Chien Wu, Shiaofen Fang, Olaf Sporns, Andrew J. Saykin, Joaquín Goñi, Li Shen:
Joint exploration and mining of memory-relevant brain anatomic and connectomic patterns via a three-way association model. 6-9 - Jian Fang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang:
Detection of differentially developed functional connectivity patterns in adolescents based on tensor discriminative analysis. 10-14 - Jian Li, Soyoung Choi, Anand A. Joshi, Jessica L. Wisnowski, Richard M. Leahy:
Global PDF-based temporal non-local means filtering reveals individual differences in brain connectivity. 15-19 - Hyekyoung Lee, Moo K. Chung, Hyejin Kang, Hongyoon Choi, Yu Kyeong Kim, Dong Soo Lee:
Abnormal hole detection in brain connectivity by kernel density of persistence diagram and Hodge Laplacian. 20-23 - Ran Shadmi, Victoria Mazo, Orna Bregman-Amitai, Eldad Elnekave:
Fully-convolutional deep-learning based system for coronary calcium score prediction from non-contrast chest CT. 24-28 - Tianyou Dou, Lijuan Zhang, Wu Zhou:
3D deep feature fusion in contrast-enhanced MR for malignancy characterization of hepatocellular carcinoma. 29-33 - Jianfei Liu, Haewon Jung, Johnny Tam:
Computer-aided detection of pattern changes in longitudinal adaptive optics images of the retinal pigment epithelium. 34-38 - Yair Dgani, Hayit Greenspan, Jacob Goldberger:
Training a neural network based on unreliable human annotation of medical images. 39-42 - Yanwu Xu, Lixin Duan, Huazhu Fu, Zhuo Zhang, Wei Zhao, Tianyuan You, Tien Yin Wong, Jiang Liu:
Ocular disease detection from multiple informatics domains. 43-47 - Claire Yilin Lin, Jeffrey A. Fessler:
Accelerated methods for low-rank plus sparse image reconstruction. 48-51 - Zhipeng Li, Saiprasad Ravishankar, Yong Long, Jeffrey A. Fessler:
Image-domain material decomposition using data-driven sparsity models for dual-energy CT. 52-56 - Christian Hauke, Martino Leghissa, Thomas Mertelmeier, Marcus Radicke, S. Sutter, Thomas Weber, Gisela Anton, Ludwig Ritschl:
Moiré artefact reduction in Talbot-Lau X-ray imaging. 57-60 - Tae Hyung Kim, Justin P. Haldar:
The Fourier radial error spectrum plot: A more nuanced quantitative evaluation of image reconstruction quality. 61-64 - Michael T. McCann, Laura Vilaclara, Michael Unser:
Region of interest X-ray computed tomography via corrected back projection. 65-69 - Huan Liu, Shijie Zhao, Xi Jiang, Shu Zhang, Xintao Hu, Lei Quo, Tianming Liu:
Characterizing task-evoked and intrinsic functional networks from task-based fMRI data via two-stage sparse dictionary learning. 70-73 - Fangfei Ge, Jinglei Lv, Xintao Hu, Lei Guo, Junwei Han, Shijie Zhao, Tianming Liu:
Exploring intrinsic networks and their interactions using group wise temporal sparse coding. 74-77 - Heng Huang, Xintao Hu, Qinglin Dong, Shijie Zhao, Shu Zhang, Yu Zhao, Lei Quo, Tianming Liu:
Modeling task fMRI data via mixture of deep expert networks. 82-86 - Siyuan Gao, Abigail S. Greene, R. Todd Constable, Dustin Scheinost:
Task integration for connectome-based prediction via canonical correlation analysis. 87-91 - Junqi Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang:
Integration of network topological features and graph Fourier transform for fMRI data analysis. 92-96 - Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Daniel Y.-J. Yang, Pamela Ventola, James S. Duncan:
Prediction of Pivotal response treatment outcome with task fMRI using random forest and variable selection. 97-100 - Hongming Li, Theodore D. Satterthwaite, Yong Fan:
Brain age prediction based on resting-state functional connectivity patterns using convolutional neural networks. 101-104 - Aiying Zhang, Jian Fang, Vince D. Calhoun, Yu-Ping Wang:
High dimensional latent Gaussian copula model for mixed data in imaging genetics. 105-109 - Colin J. Brown, Jeremy Kawahara, Ghassan Hamarneh:
Connectome priors in deep neural networks to predict autism. 110-113 - Abdullah Alchihabi, Baran B. Kivilicim, Sharlene D. Newman, Fatos T. Yarman-Vural:
A dynamic network representation of fMRI for modeling and analyzing the problem solving task. 114-117 - Matthew Cieslak, Wendy Meiring, Tegan Brennan, Clint Greene, Lukas J. Volz, Jean M. Vettel, Subhash Suri, Scott T. Grafton:
Compositional measures of diffusion anisotropy and asymmetry. 123-126 - Wei Zhang, Jinglei Lv, Shu Zhang, Yu Zhao, Tianming Liu:
Modeling resting state fMRI data via longitudinal supervised stochastic coordinate coding. 127-131 - Daniel Schmitz, Katrin Amunts, Thomas Lippert, Markus Axer:
A least squares approach for the reconstruction of nerve fiber orientations from tiltable specimen experiments in 3D-PLI. 132-135 - Guodong Zeng, Guoyan Zheng:
Multi-stream 3D FCN with multi-scale deep supervision for multi-modality isointense infant brain MR image segmentation. 136-140 - Sudhanya Chatterjee, Olivier Commowick, Onur Afacan, Simon K. Warfield, Christian Barillot:
Multi-compartment model of brain tissues from T2 relaxometry MRI using gamma distribution. 141-144 - Shubham Kumar, Sailesh Conjeti, Abhijit Guha Roy, Christian Wachinger, Nassir Navab:
InfiNet: Fully convolutional networks for infant brain MRI segmentation. 145-148 - Karl Bäckström, Mahmood Nazari, Irene Yu-Hua Gu, Asgeir Store Jakola:
An efficient 3D deep convolutional network for Alzheimer's disease diagnosis using MR images. 149-153 - Qiang Zheng, Yong Fan:
Integrating semi-supervised label propagation and random forests for multi-atlas based hippocampus segmentation. 154-157 - Snehashis Roy, John A. Butman, Leighton Chan, Dzung L. Pham:
TBI contusion segmentation from MRI using convolutional neural networks. 158-162 - Francisco Javier Alvarez Padilla, Barbara Romaniuk, Benoît Naegel, Stéphanie Servagi-Vernat, David Morland, Dimitri Papathanassiou, Nicolas Passat:
Hierarchical forest attributes for multimodal tumor segmentation on FDG-PET/contrast-enhanced CT. 163-167 - Noel C. F. Codella, David A. Gutman, M. Emre Celebi, Brian Helba, Michael A. Marchetti, Stephen W. Dusza, Aadi Kalloo, Konstantinos Liopyris, Nabin K. Mishra, Harald Kittler, Allan Halpern:
Skin lesion analysis toward melanoma detection: A challenge at the 2017 International symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC). 168-172 - Marek Wodzinski, Andrzej Skalski, Izabela Ciepiela, Tomasz Kuszewski, Piotr Kedzierawski:
Volume regularization in explicit image registration used for breast cancer bed localization. 173-176 - Anneke Meyer, Alireza Mehrtash, Marko Rak, Daniel Schindele, Martin Schostak, Clare M. Tempany, Tina Kapur, Purang Abolmaesumi, Andriy Fedorov, Christian Hansen:
Automatic high resolution segmentation of the prostate from multi-planar MRI. 177-181 - Yuexiang Li, Xuechen Li, Xinpeng Xie, Linlin Shen:
Deep learning based gastric cancer identification. 182-185 - Korsuk Sirinukunwattana, J. Lin, P. Lu, F. Beca, J. Peng, A. Tolwani, A. Stancu, Sushama Varma, Robert West:
Quantifying chromosomal copy number alterations in breast ductal carcinoma in situ: A deep learning based approach. 186-190 - Ida Arvidsson, Niels Christian Overgaard, Felicia-Elena Marginean, Agnieszka Krzyzanowska, Anders Bjartell, Kalle Åström, Anders Heyden:
Generalization of prostate cancer classification for multiple sites using deep learning. 191-194 - Yi-Jie Huang, Qi Dou, Zi-Xian Wang, Li-Zhi Liu, Li-Sheng Wang, Hao Chen, Pheng-Ann Heng, Rui-Hua Xu:
HL-FCN: Hybrid loss guided FCN for colorectal cancer segmentation. 195-198 - Wei Shao, Liang Sun, Daoqiang Zhang:
Deep active learning for nucleus classification in pathology images. 199-202 - Xuelu Li, Vishal Monga, Arvind U. K. Rao:
Analysis-synthesis model learning with shared features: A new framework for histopathological image classification. 203-206 - Islam Reda, Babajide O. Ayinde, Mohammed M. Elmogy, Ahmed Shalaby, Moumen T. El-Melegy, Mohamed Abou El-Ghar, Ahmed Abou El-Fetouh, Mohammed Ghazal, Ayman El-Baz:
A new CNN-based system for early diagnosis of prostate cancer. 207-210 - Olmo Zavala-Romero, Anke Meyer-Baese, Marc B. I. Lobbes:
Breast lesion segmentation software for DCE-MRI: An open source GPGPU based optimization. 211-215 - Faisal Mahmood, Nicholas J. Durr:
Topographical reconstructions from monocular optical colonoscopy images via deep learning. 216-219 - Chunfeng Lian, Hua Li, Pierre Vera, Su Ruan:
Unsupervised co-segmentation of tumor in PET-CT images using belief functions based fusion. 220-223 - Zisha Zhong, Yusung Kim, Leixin Zhou, Kristin A. Plichta, Bryan Allen, John M. Buatti, Xiaodong Wu:
Improving tumor co-segmentation on PET-CT images with 3D co-matting. 224-227 - Zisha Zhong, Yusung Kim, Leixin Zhou, Kristin A. Plichta, Bryan Allen, John M. Buatti, Xiaodong Wu:
3D fully convolutional networks for co-segmentation of tumors on PET-CT images. 228-231 - Deepak Roy Chittajallu, Neal Siekierski, Sanghoon Lee, Samuel Gerber, Jonathan D. Beezley, David Manthey, David A. Gutman, Lee A. D. Cooper:
Vectorized persistent homology representations for characterizing glandular architecture in histology images. 232-235 - Nan Chen, Chaan Ng, Brian Paul Hobbs:
Bayesian classifiers of solid lesions with dynamic CT: Integrating enhancement density with washout density and delay interval. 236-239 - Maria J. M. Chuquicusma, Sarfaraz Hussein, Jeremy Burt, Ulas Bagci:
How to fool radiologists with generative adversarial networks? A visual turing test for lung cancer diagnosis. 240-244 - Mariëlle J. A. Jansen, Hugo J. Kuijf, Josien P. W. Pluim:
Automatic classification of focal liver lesions based on clinical DCE-MR and T2-weighted images: A feasibility study. 245-248 - Dejan Knez, Imad S. Nahle, Tomaz Vrtovec, Stefan Parent, Samuel Kadoury:
Computer-assisted pedicle screw placement planning: Towards clinical practice. 249-252 - Maria V. Sainz de Cea, Yongyi Yang, Robert M. Nishikawa:
Reducing the effect of false positives in classification of detected clustered microcalcifications. 253-256 - Yang Song, Hang Chang, Yang Gao, Sidong Liu, Donghao Zhang, Junen Yao, Wojciech Chrzanowski, Weidong Cai:
Feature learning with component selective encoding for histopathology image classification. 257-260 - Yan Zhuang, Omar Uribe, Mark M. McDonald, Iris Lin, Daniel Arteaga, William Dalrymple, Bradford Worrall, Andrew Southerland, Gustavo K. Rohde:
Pathological facial weakness detection using computational image analysis. 261-264 - P. M. Gordaliza, Juan José Vaquero, Sally Sharpe, Manuel Desco, Arrate Muñoz-Barrutia:
Towards an informational model for tuberculosis lesion discrimination on X-ray CT images. 265-268 - Dário Augusto Borges Oliveira, Matheus Palhares Viana:
An efficient multi-scale data representation method for lung nodule false positive reduction using convolutional neural networks. 269-272 - Monica Iturrioz Campo, Javier Pascau, Raúl San José Estépar:
Emphysema quantification on simulated X-rays through deep learning techniques. 273-276 - Rong Zhang, Qiufang Liu, Hui Cui, Xiuying Wang, Shaoli Song, Gang Huang, Dagan Feng:
Thyroid classification via new multi-channel feature association and learning from multi-modality MRI images. 277-280 - Monika Grewal, Muktabh Mayank Srivastava, Pulkit Kumar, Srikrishna Varadarajan:
RADnet: Radiologist level accuracy using deep learning for hemorrhage detection in CT scans. 281-284 - Valentina Giannini, Samanta Rosati, Cristina Castagneri, Laura Martincich, Daniele Regge, Gabriella Balestra:
Radiomics for pretreatment prediction of pathological response to neoadjuvant therapy using magnetic resonance imaging: Influence of feature selection. 285-288 - Maayan Frid-Adar, Eyal Klang, Michal Amitai, Jacob Goldberger, Hayit Greenspan:
Synthetic data augmentation using GAN for improved liver lesion classification. 289-293 - Mostafa Mohamad, Amal Farag, Asem M. Ali, Salwa Elshazly, Aly A. Farag, Mohamad Ghanoum:
Enhancing virtual colonoscopy with a new visualization measure. 294-297 - Jian Wu, Su Ruan, Chunfeng Lian, Sasa Mutic, Mark A. Anastasio, Hua Li:
Active learning with noise modeling for medical image annotation. 298-301 - Prachi H. Kulkarni, S. N. Merchant, Suyash P. Awate:
Bayesian reconstruction of R-fMRI from K-T undersampled data using a robust, subject-invariant, spatially-regularized dictionary prior. 302-306 - Tomasz Pieciak, Inaki Rabanillo-Viloria, Santiago Aja-Fernández:
Bias correction for non-stationary noise filtering in MRI. 307-310 - Eunhee Kang, Jong Chul Ye:
Framelet denoising for low-dose CT using deep learning. 311-314 - Serhat Ilbey, Can Baris Top, Alper Gungor, Emine Ulku Saritas, H. Emre Guven:
Coded scenes for fast system calibration in magnetic particle imaging. 315-318 - James R. Clough, Daniel R. Balfour, Paul K. Marsden, Claudia Prieto, Andrew J. Reader, Andrew P. King:
MRI slice stacking using manifold alignment and wave kernel signatures. 319-323 - Chao Song, Yongyi Yang, Albert J. Ramon, Miles N. Wernick, P. Hendrik Pretorius, Michael A. King:
Improving perfusion defect detection with respiratory motion compensation in cardiac SPECT. 324-327 - C. Goubet, Max Langer, Françoise Peyrin, Juan F. P. J. Abascal:
Low-dose synchrotron nano-CT via compressed sensing. 328-331 - Thanh Nguyen-Duc, Won-Ki Jeong:
Compressed sensing dynamic MRI reconstruction using multi-scale 3D convolutional sparse coding with elastic net regularization. 332-335 - Tom Hohweiller, Nicolas Ducros, Françoise Peyrin, Bruno Sixou:
A constrained Gauss-Newton algorithm for material decomposition in spectral computed tomography. 336-339 - Cong Zhao, Yuncheng Zhong, Jing Wang, Mingwu Jin:
Modified simultaneous motion estimation and image reconstruction (m-SMEIR) for 4D-CBCT. 340-343 - Lianli Liu, Adam Johansson, James M. Balter, Yue Cao, Jeffrey A. Fessler:
Accelerated high b-value diffusion-weighted MR imaging via phase-constrained low-rank tensor model. 344-348 - Peng Liu, Ruogu Fang:
SDCNet: Smoothed dense-convolution network for restoring low-dose cerebral CT perfusion. 349-352 - Awais Mansoor, Teerit Vongkovit, Marius George Linguraru:
Adversarial approach to diagnostic quality volumetric image enhancement. 353-356 - Haris Jeelani, Jonathan Martin, Francis Vasquez, Michael Salerno, Daniel S. Weller:
Image quality affects deep learning reconstruction of MRI. 357-360 - Kyong Hwan Jin, Michael Unser:
3D BBPConvNet to reconstruct parallel MRI. 361-364 - Can Zhao, Aaron Carass, Blake E. Dewey, Jerry L. Prince:
Self super-resolution for magnetic resonance images using deep networks. 365-368 - Rikkert Van Durme, Annelies Coene, Guillaume Crevecoeur, Luc Dupré:
Model-based optimal design of a magnetic nanoparticle tomographic imaging setup. 369-372 - Jingru Yi, Pengxiang Wu, Daniel J. Hoeppner, Dimitris N. Metaxas:
Pixel-wise neural cell instance segmentation. 373-377 - Chi Xiao, Jing Liu, Xi Chen, Hua Han, Chang Shu, Qiwei Xie:
Deep contextual residual network for electron microscopy image segmentation in connectomics. 378-381 - Johannes Stegmaier, Thiago Vallin Spina, Alexandre X. Falcão, Andreas Bartschat, Ralf Mikut, Elliot Meyerowitz, Alexandre Cunha:
Cell segmentation in 3D confocal images using supervoxel merge-forests with CNN-based hypothesis selection. 382-386 - Damian J. Matuszewski, Ida-Maria Sintorn:
Minimal annotation training for segmentation of microscopy images. 387-390 - Thiago Vallin Spina, Johannes Stegmaier, Alexandre X. Falcão, Elliot Meyerowitz, Alexandre Cunha:
SEGMENT3D: A web-based application for collaborative segmentation of 3D images used in the shoot apical meristem. 391-395 - D. Baltissen, Thomas Wollmann, Manuel Gunkel, Inn Chung, Holger Erfle, Karsten Rippe, Karl Rohr:
Comparison of segmentation methods for tissue microscopy images of glioblastoma cells. 396-399 - Róger Bermúdez-Chacón, Pablo Márquez-Neila, Mathieu Salzmann, Pascal Fua:
A domain-adaptive two-stream U-Net for electron microscopy image segmentation. 400-404 - Matthew Quay, Zeyad Ali Sami Emam, Adam Anderson, Richard Leapman:
Designing deep neural networks to automate segmentation for serial block-face electron microscopy. 405-408 - Donghao Zhang, Yang Song, Siqi Liu, Dagan Feng, Yue Wang, Weidong Cai:
Nuclei instance segmentation with dual contour-enhanced adversarial network. 409-412 - Carlos Castilla, Martin Maska, Dmitry V. Sorokin, Erik Meijering, Carlos Ortiz-de-Solorzano:
Segmentation of actin-stained 3D fluorescent cells with filopodial protrusions using convolutional neural networks. 413-417 - David Joon Ho, Chichen Fu, Paul Salama, Kenneth W. Dunn, Edward J. Delp:
Nuclei detection and segmentation of fluorescence microscopy images using three dimensional convolutional neural networks. 418-422 - Yousef Al-Kofahi, Fiona Ginty:
Image analytic algorithms for automated cell segmentation quality control. 423-426 - Enrico Grisan, Jean-Marie Graïc, Livio Corain, Antonella Peruffo:
Resolving single cells in heavily clustered Nissl-stained images for the analysis of brain cytoarchitecture. 427-430 - Pol del Aguila Pla, Joakim Jaldén:
Cell detection on image-based immunoassays. 431-435 - Chang Shu, Xi Chen, Qiwei Xie, Chi Xiao, Hua Han:
Non-iterative simultaneous rigid registration method for serial sections of biological tissue. 436-440 - Jing Qin, Xiyu Yi, Shimon Weiss:
A novel fluorescence microscopy image deconvolution approach. 441-444 - Joseph Boyd, Alice Pinhiero, Elaine Del Nery, Fabien Reyal, Thomas Walter:
Analysing double-strand breaks in cultured cells for drug screening applications by causal inference. 445-448 - Jorge Sola-Pikabea, Ana Doblas, Genaro Saavedra, Manuel Martínez-Corral, Chrysanthe Preza:
Optimal design of incoherent tunable-frequency structured illumination microscope scheme. 449-452 - Lopamudra Mukherjee, Adib Keikhosravi, Kevin W. Eliceiri:
Neighborhood regularized image superresolution for applications to microscopic imaging. 453-457 - Yao Yao, Ihor Smal, Erik Meijering:
Deep neural networks for data association in particle tracking. 458-461 - Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, Matthew Sinclair, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Automatic left ventricular outflow tract classification for accurate cardiac MR planning. 462-465 - Siming Yan, Feng Shi, Yuhua Chen, Damini Dey, Sang-Eun Lee, Hyuk-Jae Chang, Debiao Li, Yibin Xie:
Calcium removal from cardiac ct images using deep convolutional neural network. 466-469 - Dongqing Zhang, Ilknur Icke, Belma Dogdas, Sarayu Parimal, Smita Sampath, Joseph Forbes, Ansuman Bagchi, Chih-Liang Chin, Antong Chen:
A multi-level convolutional LSTM model for the segmentation of left ventricle myocardium in infarcted porcine cine MR images. 470-473 - Ilya A. Verzhbinsky, Patrick Magrath, Eric Aliotta, Daniel B. Ennis, Luigi E. Perotti:
Time resolved displacement-based registration of in vivo cDTI cardiomyocyte orientations. 474-478 - Dong Yang, Qiaoying Huang, Leon Axel, Dimitris N. Metaxas:
Multi-component deformable models coupled with 2D-3D U-Net for automated probabilistic segmentation of cardiac walls and blood. 479-483 - Tim Tsz-Kit Lau, Emilie Chouzenoux, Claire Lefort, Jean-Christophe Pesquet:
Optimal multivariate Gaussian fitting for PSF modeling in two-photon microscopy. 484-488 - Anna Jezierska, Hugues Talbot, Jean-Christophe Pesquet:
Spatially variant PSF modeling in confocal macroscopy. 489-492 - Bertha Mayela Toledo Acosta, Xavier Heiligenstein, Grégoire Malandain, Patrick Bouthemy:
Intensity-based matching and registration for 3D correlative microscopy with large discrepancies. 493-496 - Sanjay Viswanath, Simon de Beco, Maxime Dahan, Muthuvel Arigovindan:
Multi-resolution based spatially adaptive multi-order total variation for image restoration. 497-500 - Jizhou Li, Feng Xue, Thierry Blu:
Accurate 3D PSF estimation from a wide-field microscopy image. 501-504 - Tianyi Zhao, Dashan Gao, Jiao Wang, Zhaozheng Yin:
Lung segmentation in CT images using a fully convolutional neural network with multi-instance and conditional adversary loss. 505-509 - Silas Nyboe Ørting, Jens Petersen, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne:
Detecting emphysema with multiple instance learning. 510-513