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51. Automated Unsupervised Segmentation of Liver Lesions in CT scans via Cahn-Hilliard Phase Separation

Author

Lipková, Jana, Rempfler, Markus, Christ, Patrick, Lowengrub, John, and Menze, Bjoern H.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The segmentation of liver lesions is crucial for detection, diagnosis and monitoring progression of liver cancer. However, design of accurate automated methods remains challenging due to high noise in CT scans, low contrast between liver and lesions, as well as large lesion variability. We propose a 3D automatic, unsupervised method for liver lesions segmentation using a phase separation approach. It is assumed that liver is a mixture of two phases: healthy liver and lesions, represented by different image intensities polluted by noise. The Cahn-Hilliard equation is used to remove the noise and separate the mixture into two distinct phases with well-defined interfaces. This simplifies the lesion detection and segmentation task drastically and enables to segment liver lesions by thresholding the Cahn-Hilliard solution. The method was tested on 3Dircadb and LITS dataset.

Published
2017

52. A Localisation-Segmentation Approach for Multi-label Annotation of Lumbar Vertebrae using Deep Nets

Author

Sekuboyina, Anjany, Valentinitsch, Alexander, Kirschke, Jan S., and Menze, Bjoern H.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Multi-class segmentation of vertebrae is a non-trivial task mainly due to the high correlation in the appearance of adjacent vertebrae. Hence, such a task calls for the consideration of both global and local context. Based on this motivation, we propose a two-staged approach that, given a computed tomography dataset of the spine, segments the five lumbar vertebrae and simultaneously labels them. The first stage employs a multi-layered perceptron performing non-linear regression for locating the lumbar region using the global context. The second stage, comprised of a fully-convolutional deep network, exploits the local context in the localised lumbar region to segment and label the lumbar vertebrae in one go. Aided with practical data augmentation for training, our approach is highly generalisable, capable of successfully segmenting both healthy and abnormal vertebrae (fractured and scoliotic spines). We consistently achieve an average Dice coefficient of over 90 percent on a publicly available dataset of the xVertSeg segmentation challenge of MICCAI 2016. This is particularly noteworthy because the xVertSeg dataset is beset with severe deformities in the form of vertebral fractures and scoliosis.

Published
2017

53. Efficient Algorithms for Moral Lineage Tracing

Author

Rempfler, Markus, Lange, Jan-Hendrik, Jug, Florian, Blasse, Corinna, Myers, Eugene W., Menze, Bjoern H., and Andres, Bjoern

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Lineage tracing, the joint segmentation and tracking of living cells as they move and divide in a sequence of light microscopy images, is a challenging task. Jug et al. have proposed a mathematical abstraction of this task, the moral lineage tracing problem (MLTP), whose feasible solutions define both a segmentation of every image and a lineage forest of cells. Their branch-and-cut algorithm, however, is prone to many cuts and slow convergence for large instances. To address this problem, we make three contributions: (i) we devise the first efficient primal feasible local search algorithms for the MLTP, (ii) we improve the branch-and-cut algorithm by separating tighter cutting planes and by incorporating our primal algorithms, (iii) we show in experiments that our algorithms find accurate solutions on the problem instances of Jug et al. and scale to larger instances, leveraging moral lineage tracing to practical significance., Comment: Accepted at ICCV 2017

Published
2017

54. A new protocol for multispecies bacterial infections in zebrafish and their monitoring through automated image analysis.

Author

Schmitz, Désirée A., Wechsler, Tobias, Li, Hongwei Bran, Menze, Bjoern H., and Kümmerli, Rolf

Subjects
IMAGE analysis, PATHOLOGY, ZEBRA danio, BACTERIAL diseases, INNER ear
Abstract

The zebrafish Danio rerio has become a popular model host to explore disease pathology caused by infectious agents. A main advantage is its transparency at an early age, which enables live imaging of infection dynamics. While multispecies infections are common in patients, the zebrafish model is rarely used to study them, although the model would be ideal for investigating pathogen-pathogen and pathogen-host interactions. This may be due to the absence of an established multispecies infection protocol for a defined organ and the lack of suitable image analysis pipelines for automated image processing. To address these issues, we developed a protocol for establishing and tracking single and multispecies bacterial infections in the inner ear structure (otic vesicle) of the zebrafish by imaging. Subsequently, we generated an image analysis pipeline that involved deep learning for the automated segmentation of the otic vesicle, and scripts for quantifying pathogen frequencies through fluorescence intensity measures. We used Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae, three of the difficult-to-treat ESKAPE pathogens, to show that our infection protocol and image analysis pipeline work both for single pathogens and pairwise pathogen combinations. Thus, our protocols provide a comprehensive toolbox for studying single and multispecies infections in real-time in zebrafish. [ABSTRACT FROM AUTHOR]

Published
2024
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55. Velocity-To-Pressure (V2P) - Net: Inferring Relative Pressures from Time-Varying 3D Fluid Flow Velocities

Author

Shit, Suprosanna, Das, Dhritiman, Ezhov, Ivan, Paetzold, Johannes C., Sanches, Augusto F., Thuerey, Nils, Menze, Bjoern H., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Feragen, Aasa, editor, Sommer, Stefan, editor, Schnabel, Julia, editor, and Nielsen, Mads, editor

Published
2021
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57. Reliable Saliency Maps for Weakly-Supervised Localization of Disease Patterns

Author

Möller, Maximilian, Kohl, Matthias, Braunewell, Stefan, Kofler, Florian, Wiestler, Benedikt, Kirschke, Jan S., Menze, Björn H., Piraud, Marie, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cardoso, Jaime, editor, Van Nguyen, Hien, editor, Heller, Nicholas, editor, Henriques Abreu, Pedro, editor, Isgum, Ivana, editor, Silva, Wilson, editor, Cruz, Ricardo, editor, Pereira Amorim, Jose, editor, Patel, Vishal, editor, Roysam, Badri, editor, Zhou, Kevin, editor, Jiang, Steve, editor, Le, Ngan, editor, Luu, Khoa, editor, Sznitman, Raphael, editor, Cheplygina, Veronika, editor, Mateus, Diana, editor, Trucco, Emanuele, editor, and Abbasi, Samaneh, editor

Published
2020
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58. Reinforced Redetection of Landmark in Pre- and Post-operative Brain Scan Using Anatomical Guidance for Image Alignment

Author

Waldmannstetter, Diana, Navarro, Fernando, Wiestler, Benedikt, Kirschke, Jan S., Sekuboyina, Anjany, Molero, Ester, Menze, Bjoern H., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Špiclin, Žiga, editor, McClelland, Jamie, editor, Kybic, Jan, editor, and Goksel, Orcun, editor

Published
2020
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59. A Baseline for Predicting Glioblastoma Patient Survival Time with Classical Statistical Models and Primitive Features Ignoring Image Information

Author

Kofler, Florian, Paetzold, Johannes C., Ezhov, Ivan, Shit, Suprosanna, Krahulec, Daniel, Kirschke, Jan S., Zimmer, Claus, Wiestler, Benedikt, Menze, Bjoern H., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Crimi, Alessandro, editor, and Bakas, Spyridon, editor

Published
2020
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60. Vertebral Labelling in Radiographs: Learning a Coordinate Corrector to Enforce Spinal Shape

Author

Bayat, Amirhossein, Sekuboyina, Anjany, Hofmann, Felix, Husseini, Malek El, Kirschke, Jan S., Menze, Bjoern H., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cai, Yunliang, editor, Wang, Liansheng, editor, Audette, Michel, editor, Zheng, Guoyan, editor, and Li, Shuo, editor

Published
2020
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61. Conditioned Variational Auto-encoder for Detecting Osteoporotic Vertebral Fractures

Author

Husseini, Malek, Sekuboyina, Anjany, Bayat, Amirhossein, Menze, Bjoern H., Loeffler, Maximilian, Kirschke, Jan S., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cai, Yunliang, editor, Wang, Liansheng, editor, Audette, Michel, editor, Zheng, Guoyan, editor, and Li, Shuo, editor

Published
2020
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62. VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images

Author

Sekuboyina, Anjany, Husseini, Malek E., Bayat, Amirhossein, Löffler, Maximilian, Liebl, Hans, Li, Hongwei, Tetteh, Giles, Kukačka, Jan, Payer, Christian, Štern, Darko, Urschler, Martin, Chen, Maodong, Cheng, Dalong, Lessmann, Nikolas, Hu, Yujin, Wang, Tianfu, Yang, Dong, Xu, Daguang, Ambellan, Felix, Amiranashvili, Tamaz, Ehlke, Moritz, Lamecker, Hans, Lehnert, Sebastian, Lirio, Marilia, Olaguer, Nicolás Pérez de, Ramm, Heiko, Sahu, Manish, Tack, Alexander, Zachow, Stefan, Jiang, Tao, Ma, Xinjun, Angerman, Christoph, Wang, Xin, Brown, Kevin, Kirszenberg, Alexandre, Puybareau, Élodie, Chen, Di, Bai, Yiwei, Rapazzo, Brandon H., Yeah, Timyoas, Zhang, Amber, Xu, Shangliang, Hou, Feng, He, Zhiqiang, Zeng, Chan, Xiangshang, Zheng, Liming, Xu, Netherton, Tucker J., Mumme, Raymond P., Court, Laurence E., Huang, Zixun, He, Chenhang, Wang, Li-Wen, Ling, Sai Ho, Huỳnh, Lê Duy, Boutry, Nicolas, Jakubicek, Roman, Chmelik, Jiri, Mulay, Supriti, Sivaprakasam, Mohanasankar, Paetzold, Johannes C., Shit, Suprosanna, Ezhov, Ivan, Wiestler, Benedikt, Glocker, Ben, Valentinitsch, Alexander, Rempfler, Markus, Menze, Björn H., and Kirschke, Jan S.

Published
2021
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63. Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields

Author

Christ, Patrick Ferdinand, Elshaer, Mohamed Ezzeldin A., Ettlinger, Florian, Tatavarty, Sunil, Bickel, Marc, Bilic, Patrick, Rempfler, Markus, Armbruster, Marco, Hofmann, Felix, D'Anastasi, Melvin, Sommer, Wieland H., Ahmadi, Seyed-Ahmad, and Menze, Bjoern H.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Automatic segmentation of the liver and its lesion is an important step towards deriving quantitative biomarkers for accurate clinical diagnosis and computer-aided decision support systems. This paper presents a method to automatically segment liver and lesions in CT abdomen images using cascaded fully convolutional neural networks (CFCNs) and dense 3D conditional random fields (CRFs). We train and cascade two FCNs for a combined segmentation of the liver and its lesions. In the first step, we train a FCN to segment the liver as ROI input for a second FCN. The second FCN solely segments lesions from the predicted liver ROIs of step 1. We refine the segmentations of the CFCN using a dense 3D CRF that accounts for both spatial coherence and appearance. CFCN models were trained in a 2-fold cross-validation on the abdominal CT dataset 3DIRCAD comprising 15 hepatic tumor volumes. Our results show that CFCN-based semantic liver and lesion segmentation achieves Dice scores over 94% for liver with computation times below 100s per volume. We experimentally demonstrate the robustness of the proposed method as a decision support system with a high accuracy and speed for usage in daily clinical routine., Comment: Accepted at MICCAI 2016. Source code available on https://github.com/IBBM/Cascaded-FCN

Published
2016
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64. The Minimum Cost Connected Subgraph Problem in Medical Image Analysis

Author

Rempfler, Markus, Andres, Bjoern, and Menze, Bjoern H.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Several important tasks in medical image analysis can be stated in the form of an optimization problem whose feasible solutions are connected subgraphs. Examples include the reconstruction of neural or vascular structures under connectedness constraints. We discuss the minimum cost connected subgraph (MCCS) problem and its approximations from the perspective of medical applications. We propose a) objective-dependent constraints and b) novel constraint generation schemes to solve this optimization problem exactly by means of a branch-and-cut algorithm. These are shown to improve scalability and allow us to solve instances of two medical benchmark datasets to optimality for the first time. This enables us to perform a quantitative comparison between exact and approximative algorithms, where we identify the geodesic tree algorithm as an excellent alternative to exact inference on the examined datasets., Comment: accepted at MICCAI 2016

Published
2016
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65. FedCostWAvg: A New Averaging for Better Federated Learning

Author

Mächler, Leon, primary, Ezhov, Ivan, additional, Kofler, Florian, additional, Shit, Suprosanna, additional, Paetzold, Johannes C., additional, Loehr, Timo, additional, Zimmer, Claus, additional, Wiestler, Benedikt, additional, and Menze, Bjoern H., additional

Published
2022
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67. Learning continuous shape priors from sparse data with neural implicit functions

Author

Amiranashvili, Tamaz; https://orcid.org/0000-0001-8914-3427, Lüdke, David, Li, Hongwei Bran; https://orcid.org/0000-0002-5328-6407, Zachow, Stefan; https://orcid.org/0000-0001-7964-3049, Menze, Bjoern H; https://orcid.org/0000-0003-4136-5690, Amiranashvili, Tamaz; https://orcid.org/0000-0001-8914-3427, Lüdke, David, Li, Hongwei Bran; https://orcid.org/0000-0002-5328-6407, Zachow, Stefan; https://orcid.org/0000-0001-7964-3049, and Menze, Bjoern H; https://orcid.org/0000-0003-4136-5690

Published
2024

69. Shape-Aware Complementary-Task Learning for Multi-organ Segmentation

Author

Navarro, Fernando, Shit, Suprosanna, Ezhov, Ivan, Paetzold, Johannes, Gafita, Andrei, Peeken, Jan C., Combs, Stephanie E., Menze, Bjoern H., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Suk, Heung-Il, editor, Liu, Mingxia, editor, Yan, Pingkun, editor, and Lian, Chunfeng, editor

Published
2019
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70. Hierarchical Multi-class Segmentation of Glioma Images Using Networks with Multi-level Activation Function

Author

Hu, Xiaobin, Li, Hongwei, Zhao, Yu, Dong, Chao, Menze, Bjoern H., Piraud, Marie, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Crimi, Alessandro, editor, Bakas, Spyridon, editor, Kuijf, Hugo, editor, Keyvan, Farahani, editor, Reyes, Mauricio, editor, and van Walsum, Theo, editor

Published
2019
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71. Multi-level Activation for Segmentation of Hierarchically-Nested Classes

Author

Piraud, Marie, Sekuboyina, Anjany, Menze, Björn H., Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Leal-Taixé, Laura, editor, and Roth, Stefan, editor

Published
2019
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72. Radiotherapy planning for glioblastoma based on a tumor growth model: Improving target volume delineation

Author

Unkelbach, Jan, Menze, Bjoern H., Konukoglu, Ender, Dittmann, Florian, Le, Matthieu, Ayache, Nicholas, and Shih, Helen A.

Subjects
Physics - Medical Physics
Abstract

Glioblastoma are known to infiltrate the brain parenchyma instead of forming a solid tumor mass with a defined boundary. Only the part of the tumor with high tumor cell density can be localized through imaging directly. In contrast, brain tissue infiltrated by tumor cells at low density appears normal on current imaging modalities. In clinical practice, a uniform margin is applied to account for microscopic spread of disease. The current treatment planning procedure can potentially be improved by accounting for the anisotropy of tumor growth: Anatomical barriers such as the falx cerebri represent boundaries for migrating tumor cells. In addition, tumor cells primarily spread in white matter and infiltrate gray matter at lower rate. We investigate the use of a phenomenological tumor growth model for treatment planning. The model is based on the Fisher-Kolmogorov equation, which formalizes these growth characteristics and estimates the spatial distribution of tumor cells in normal appearing regions of the brain. The target volume for radiotherapy planning can be defined as an isoline of the simulated tumor cell density. A retrospective study involving 10 glioblastoma patients has been performed. To illustrate the main findings of the study, a detailed case study is presented for a glioblastoma located close to the falx. In this situation, the falx represents a boundary for migrating tumor cells, whereas the corpus callosum provides a route for the tumor to spread to the contralateral hemisphere. We further discuss the sensitivity of the model with respect to the input parameters. Correct segmentation of the brain appears to be the most crucial model input. We conclude that the tumor growth model provides a method to account for anisotropic growth patterns of glioblastoma, and may therefore provide a tool to make target delineation more objective and automated.

Published
2013
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74. Attention-Driven Deep Learning for Pathological Spine Segmentation

Author

Sekuboyina, Anjany, Kukačka, Jan, Kirschke, Jan S., Menze, Bjoern H., Valentinitsch, Alexander, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Glocker, Ben, editor, Yao, Jianhua, editor, Vrtovec, Tomaž, editor, Frangi, Alejandro, editor, and Zheng, Guoyan, editor

Published
2018
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75. Deep Learning with Synthetic Diffusion MRI Data for Free-Water Elimination in Glioblastoma Cases

Author

Molina-Romero, Miguel, Wiestler, Benedikt, Gómez, Pedro A., Menzel, Marion I., Menze, Bjoern H., Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Frangi, Alejandro F., editor, Schnabel, Julia A., editor, Davatzikos, Christos, editor, Alberola-López, Carlos, editor, and Fichtinger, Gabor, editor

Published
2018
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84. Focused Decoding Enables 3D Anatomical Detection by Transformers

Author

Wittmann, Bastian, Navarro, Fernando, Shit, Suprosanna, Menze, Bjoern H, and University of Zurich

Subjects
FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 610 Medicine & health, 11493 Department of Quantitative Biomedicine
Abstract

Detection Transformers represent end-to-end object detection approaches based on a Transformer encoder-decoder architecture, exploiting the attention mechanism for global relation modeling. Although Detection Transformers deliver results on par with or even superior to their highly optimized CNN-based counterparts operating on 2D natural images, their success is closely coupled to access to a vast amount of training data. This, however, restricts the feasibility of employing Detection Transformers in the medical domain, as access to annotated data is typically limited. To tackle this issue and facilitate the advent of medical Detection Transformers, we propose a novel Detection Transformer for 3D anatomical structure detection, dubbed Focused Decoder. Focused Decoder leverages information from an anatomical region atlas to simultaneously deploy query anchors and restrict the cross-attention's field of view to regions of interest, which allows for a precise focus on relevant anatomical structures. We evaluate our proposed approach on two publicly available CT datasets and demonstrate that Focused Decoder not only provides strong detection results and thus alleviates the need for a vast amount of annotated data but also exhibits exceptional and highly intuitive explainability of results via attention weights. Our code is available at https://github.com/bwittmann/transoar., Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2023:003

Published
2023

85. Multi-modal Image Classification Using Low-Dimensional Texture Features for Genomic Brain Tumor Recognition

Author

Alberts, Esther, Tetteh, Giles, Trebeschi, Stefano, Bieth, Marie, Valentinitsch, Alexander, Wiestler, Benedikt, Zimmer, Claus, Menze, Bjoern H., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Cardoso, M. Jorge, editor, Arbel, Tal, editor, Ferrante, Enzo, editor, Pennec, Xavier, editor, Dalca, Adrian V., editor, Parisot, Sarah, editor, Joshi, Sarang, editor, Batmanghelich, Nematollah K., editor, Sotiras, Aristeidis, editor, Nielsen, Mads, editor, Sabuncu, Mert R., editor, Fletcher, Tom, editor, Shen, Li, editor, Durrleman, Stanley, editor, and Sommer, Stefan, editor

Published
2017
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86. Uncertainty Estimation in Vascular Networks

Author

Rempfler, Markus, Andres, Bjoern, Menze, Bjoern H., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Cardoso, M. Jorge, editor, Arbel, Tal, editor, Ferrante, Enzo, editor, Pennec, Xavier, editor, Dalca, Adrian V., editor, Parisot, Sarah, editor, Joshi, Sarang, editor, Batmanghelich, Nematollah K., editor, Sotiras, Aristeidis, editor, Nielsen, Mads, editor, Sabuncu, Mert R., editor, Fletcher, Tom, editor, Shen, Li, editor, Durrleman, Stanley, editor, and Sommer, Stefan, editor

Published
2017
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87. Cell Lineage Tracing in Lens-Free Microscopy Videos

Author

Rempfler, Markus, Kumar, Sanjeev, Stierle, Valentin, Paulitschke, Philipp, Andres, Bjoern, Menze, Bjoern H., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Descoteaux, Maxime, editor, Maier-Hein, Lena, editor, Franz, Alfred, editor, Jannin, Pierre, editor, Collins, D. Louis, editor, and Duchesne, Simon, editor

Published
2017
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88. Quantification of Metabolites in Magnetic Resonance Spectroscopic Imaging Using Machine Learning

Author

Das, Dhritiman, Coello, Eduardo, Schulte, Rolf F., Menze, Bjoern H., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Descoteaux, Maxime, editor, Maier-Hein, Lena, editor, Franz, Alfred, editor, Jannin, Pierre, editor, Collins, D. Louis, editor, and Duchesne, Simon, editor

Published
2017
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89. Robust Reconstruction of Accelerated Perfusion MRI Using Local and Nonlocal Constraints

Author

Ulas, Cagdas, Gómez, Pedro A., Krahmer, Felix, Sperl, Jonathan I., Menzel, Marion I., Menze, Bjoern H., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Zuluaga, Maria A., editor, Bhatia, Kanwal, editor, Kainz, Bernhard, editor, Moghari, Mehdi H., editor, and Pace, Danielle F., editor

Published
2017
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92. Virtual reality empowered deep learning analysis of brain activity

Author

Kaltenecker, Doris, primary, Al-Maskari, Rami, additional, Negwer, Moritz, additional, Hoeher, Luciano, additional, Kofler, Florian, additional, Zhao, Shan, additional, Todorov, Mihail Todorov, additional, Paetzold, Johannes Christian, additional, Wiestler, Benedikt, additional, Geppert, Julia, additional, Morigny, Pauline, additional, Rohm, Maria, additional, Menze, Bjoern H., additional, Herzig, Stephan, additional, Berriel Diaz, Mauricio, additional, and Erturk, Ali, additional

Published
2023
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93. A Nonparametric Growth Model for Brain Tumor Segmentation in Longitudinal MR Sequences

Author

Alberts, Esther, Charpiat, Guillaume, Tarabalka, Yuliya, Huber, Thomas, Weber, Marc-André, Bauer, Jan, Zimmer, Claus, Menze, Bjoern H., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Crimi, Alessandro, editor, Menze, Bjoern, editor, Maier, Oskar, editor, Reyes, Mauricio, editor, and Handels, Heinz, editor

Published
2016
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94. Stroke Lesion Segmentation Using a Probabilistic Atlas of Cerebral Vascular Territories

Author

Derntl, Alexandra, Plant, Claudia, Gruber, Philipp, Wegener, Susanne, Bauer, Jan S., Menze, Bjoern H., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Crimi, Alessandro, editor, Menze, Bjoern, editor, Maier, Oskar, editor, Reyes, Mauricio, editor, and Handels, Heinz, editor

Published
2016
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95. Simultaneous Parameter Mapping, Modality Synthesis, and Anatomical Labeling of the Brain with MR Fingerprinting

Author

Gómez, Pedro A., Molina-Romero, Miguel, Ulas, Cagdas, Bounincontri, Guido, Sperl, Jonathan I., Jones, Derek K., Menzel, Marion I., Menze, Bjoern H., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Ourselin, Sebastien, editor, Joskowicz, Leo, editor, Sabuncu, Mert R., editor, Unal, Gozde, editor, and Wells, William, editor

Published
2016
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96. Spatially Adaptive Spectral Denoising for MR Spectroscopic Imaging using Frequency-Phase Non-local Means

Author

Das, Dhritiman, Coello, Eduardo, Schulte, Rolf F., Menze, Bjoern H., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Ourselin, Sebastien, editor, Joskowicz, Leo, editor, Sabuncu, Mert R., editor, Unal, Gozde, editor, and Wells, William, editor

Published
2016
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97. ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI

Author

Maier, Oskar, Menze, Bjoern H., von der Gablentz, Janina, Häni, Levin, Heinrich, Mattias P., Liebrand, Matthias, Winzeck, Stefan, Basit, Abdul, Bentley, Paul, Chen, Liang, Christiaens, Daan, Dutil, Francis, Egger, Karl, Feng, Chaolu, Glocker, Ben, Götz, Michael, Haeck, Tom, Halme, Hanna-Leena, Havaei, Mohammad, Iftekharuddin, Khan M., Jodoin, Pierre-Marc, Kamnitsas, Konstantinos, Kellner, Elias, Korvenoja, Antti, Larochelle, Hugo, Ledig, Christian, Lee, Jia-Hong, Maes, Frederik, Mahmood, Qaiser, Maier-Hein, Klaus H., McKinley, Richard, Muschelli, John, Pal, Chris, Pei, Linmin, Rangarajan, Janaki Raman, Reza, Syed M.S., Robben, David, Rueckert, Daniel, Salli, Eero, Suetens, Paul, Wang, Ching-Wei, Wilms, Matthias, Kirschke, Jan S., Krämer, Ulrike M., Münte, Thomas F., Schramm, Peter, Wiest, Roland, Handels, Heinz, and Reyes, Mauricio

Published
2017
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