Search Results for author: Lena Maier-Hein

Found 58 papers, 15 papers with code

FISBe: A Real-World Benchmark Dataset for Instance Segmentation of Long-Range Thin Filamentous Structures

no code implementations CVPR 2024 Lisa Mais, Peter Hirsch, Claire Managan, Ramya Kandarpa, Josef Lorenz Rumberger, Annika Reinke, Lena Maier-Hein, Gudrun Ihrke, Dagmar Kainmueller

Lastly we provide three baselines to kick off a competition that we envision to both advance the field of machine learning regarding methodology for capturing long-range data dependencies and facilitate scientific discovery in basic neuroscience.

Benchmarking Instance Segmentation +2

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

no code implementations11 Aug 2023 Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard O Botwe, Bishesh Khanal, Brigit Beger, Carol C Wu, Celia Cintas, Curtis P Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A González, Folkert W Asselbergs, Fred Prior, Gabriel P Krestin, Gary Collins, Geletaw S Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C Woodruf, Hugo JWL Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Islem Rekik, James Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W Gichoya, Julia A Schnabel, Kaisar Kushibar, Katrine Riklund, Kensaku MORI, Kostas Marias, Lameck M Amugongo, Lauren A Fromont, Lena Maier-Hein, Leonor Cerdá Alberich, Leticia Rittner, Lighton Phiri, Linda Marrakchi-Kacem, Lluís Donoso-Bach, Luis Martí-Bonmatí, M Jorge Cardoso, Maciej Bobowicz, Mahsa Shabani, Manolis Tsiknakis, Maria A Zuluaga, Maria Bielikova, Marie-Christine Fritzsche, Marius George Linguraru, Markus Wenzel, Marleen de Bruijne, Martin G Tolsgaard, Marzyeh Ghassemi, Md Ashrafuzzaman, Melanie Goisauf, Mohammad Yaqub, Mohammed Ammar, Mónica Cano Abadía, Mukhtar M E Mahmoud, Mustafa Elattar, Nicola Rieke, Nikolaos Papanikolaou, Noussair Lazrak, Oliver Díaz, Olivier Salvado, Oriol Pujol, Ousmane Sall, Pamela Guevara, Peter Gordebeke, Philippe Lambin, Pieta Brown, Purang Abolmaesumi, Qi Dou, Qinghua Lu, Richard Osuala, Rose Nakasi, S Kevin Zhou, Sandy Napel, Sara Colantonio, Shadi Albarqouni, Smriti Joshi, Stacy Carter, Stefan Klein, Steffen E Petersen, Susanna Aussó, Suyash Awate, Tammy Riklin Raviv, Tessa Cook, Tinashe E M Mutsvangwa, Wendy A Rogers, Wiro J Niessen, Xènia Puig-Bosch, Yi Zeng, Yunusa G Mohammed, Yves Saint James Aquino, Zohaib Salahuddin, Martijn P A Starmans

This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare.

Fairness

Challenge Results Are Not Reproducible

no code implementations14 Jul 2023 Annika Reinke, Georg Grab, Lena Maier-Hein

While clinical trials are the state-of-the-art methods to assess the effect of new medication in a comparative manner, benchmarking in the field of medical image analysis is performed by so-called challenges.

Benchmarking Image Segmentation +2

Why is the winner the best?

no code implementations CVPR 2023 Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, Ali Emre Kavur, Oldřich Kodym, Michal Kozubek, Jianning Li, Hongwei Li, Jun Ma, Carlos Martín-Isla, Bjoern Menze, Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, Jonathan Rafael-Patiño, Vivek Singh Bawa, Stefanie Speidel, Carole H. Sudre, Kimberlin Van Wijnen, Martin Wagner, Donglai Wei, Amine Yamlahi, Moi Hoon Yap, Chun Yuan, Maximilian Zenk, Aneeq Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, Jihoon Cho, Chanyeol Choi, Qi Dou, Ivan Ezhov, Christoph M. Friedrich, Clifton Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García Faura, Maria Grammatikopoulou, SeulGi Hong, Mostafa Jahanifar, Ikbeom Jang, Abdolrahim Kadkhodamohammadi, Inha Kang, Florian Kofler, Satoshi Kondo, Hugo Kuijf, Mingxing Li, Minh Huan Luu, Tomaž Martinčič, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, Subeen Pang, Jinah Park, Sung-Hong Park, Szymon Płotka, Elodie Puybareau, Nasir Rajpoot, Kanghyun Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Štepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Helene Urien, João L. Vilaça, Kareem Abdul Wahid, Haojie Wang, Jiacheng Wang, Liansheng Wang, Xiyue Wang, Benedikt Wiestler, Marek Wodzinski, Fangfang Xia, Juanying Xie, Zhiwei Xiong, Sen yang, Yanwu Yang, Zixuan Zhao, Klaus Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein

The "typical" lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning.

Benchmarking Multi-Task Learning

Deployment of Image Analysis Algorithms under Prevalence Shifts

1 code implementation22 Mar 2023 Patrick Godau, Piotr Kalinowski, Evangelia Christodoulou, Annika Reinke, Minu Tizabi, Luciana Ferrer, Paul Jäger, Lena Maier-Hein

Domain gaps are among the most relevant roadblocks in the clinical translation of machine learning (ML)-based solutions for medical image analysis.

Image Classification

Semantic segmentation of surgical hyperspectral images under geometric domain shifts

1 code implementation20 Mar 2023 Jan Sellner, Silvia Seidlitz, Alexander Studier-Fischer, Alessandro Motta, Berkin Özdemir, Beat Peter Müller-Stich, Felix Nickel, Lena Maier-Hein

According to a comprehensive validation on six different OOD data sets comprising 600 RGB and hyperspectral imaging (HSI) cubes from 33 pigs semantically annotated with 19 classes, we demonstrate a large performance drop of SOA organ segmentation networks applied to geometric OOD data.

Organ Segmentation Scene Segmentation +2

Understanding metric-related pitfalls in image analysis validation

no code implementations3 Feb 2023 Annika Reinke, Minu D. Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Acion, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew Blaschko, Florian Buettner, M. Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin Kurc, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir Rajpoot, Mauricio Reyes, Michael A. Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul F. Jäger, Lena Maier-Hein

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice.

Biomedical image analysis competitions: The state of current participation practice

no code implementations16 Dec 2022 Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Patrick Godau, Veronika Cheplygina, Michal Kozubek, Sharib Ali, Anubha Gupta, Jan Kybic, Alison Noble, Carlos Ortiz de Solórzano, Samiksha Pachade, Caroline Petitjean, Daniel Sage, Donglai Wei, Elizabeth Wilden, Deepak Alapatt, Vincent Andrearczyk, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Vivek Singh Bawa, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Jinwook Choi, Olivier Commowick, Marie Daum, Adrien Depeursinge, Reuben Dorent, Jan Egger, Hannah Eichhorn, Sandy Engelhardt, Melanie Ganz, Gabriel Girard, Lasse Hansen, Mattias Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Hyunjeong Kim, Bennett Landman, Hongwei Bran Li, Jianning Li, Jun Ma, Anne Martel, Carlos Martín-Isla, Bjoern Menze, Chinedu Innocent Nwoye, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Carole Sudre, Kimberlin Van Wijnen, Armine Vardazaryan, Tom Vercauteren, Martin Wagner, Chuanbo Wang, Moi Hoon Yap, Zeyun Yu, Chun Yuan, Maximilian Zenk, Aneeq Zia, David Zimmerer, Rina Bao, Chanyeol Choi, Andrew Cohen, Oleh Dzyubachyk, Adrian Galdran, Tianyuan Gan, Tianqi Guo, Pradyumna Gupta, Mahmood Haithami, Edward Ho, Ikbeom Jang, Zhili Li, Zhengbo Luo, Filip Lux, Sokratis Makrogiannis, Dominik Müller, Young-tack Oh, Subeen Pang, Constantin Pape, Gorkem Polat, Charlotte Rosalie Reed, Kanghyun Ryu, Tim Scherr, Vajira Thambawita, Haoyu Wang, Xinliang Wang, Kele Xu, Hung Yeh, Doyeob Yeo, Yixuan Yuan, Yan Zeng, Xin Zhao, Julian Abbing, Jannes Adam, Nagesh Adluru, Niklas Agethen, Salman Ahmed, Yasmina Al Khalil, Mireia Alenyà, Esa Alhoniemi, Chengyang An, Talha Anwar, Tewodros Weldebirhan Arega, Netanell Avisdris, Dogu Baran Aydogan, Yingbin Bai, Maria Baldeon Calisto, Berke Doga Basaran, Marcel Beetz, Cheng Bian, Hao Bian, Kevin Blansit, Louise Bloch, Robert Bohnsack, Sara Bosticardo, Jack Breen, Mikael Brudfors, Raphael Brüngel, Mariano Cabezas, Alberto Cacciola, Zhiwei Chen, Yucong Chen, Daniel Tianming Chen, Minjeong Cho, Min-Kook Choi, Chuantao Xie Chuantao Xie, Dana Cobzas, Julien Cohen-Adad, Jorge Corral Acero, Sujit Kumar Das, Marcela de Oliveira, Hanqiu Deng, Guiming Dong, Lars Doorenbos, Cory Efird, Sergio Escalera, Di Fan, Mehdi Fatan Serj, Alexandre Fenneteau, Lucas Fidon, Patryk Filipiak, René Finzel, Nuno R. Freitas, Christoph M. Friedrich, Mitchell Fulton, Finn Gaida, Francesco Galati, Christoforos Galazis, Chang Hee Gan, Zheyao Gao, Shengbo Gao, Matej Gazda, Beerend Gerats, Neil Getty, Adam Gibicar, Ryan Gifford, Sajan Gohil, Maria Grammatikopoulou, Daniel Grzech, Orhun Güley, Timo Günnemann, Chunxu Guo, Sylvain Guy, Heonjin Ha, Luyi Han, Il Song Han, Ali Hatamizadeh, Tian He, Jimin Heo, Sebastian Hitziger, SeulGi Hong, Seungbum Hong, Rian Huang, Ziyan Huang, Markus Huellebrand, Stephan Huschauer, Mustaffa Hussain, Tomoo Inubushi, Ece Isik Polat, Mojtaba Jafaritadi, SeongHun Jeong, Bailiang Jian, Yuanhong Jiang, Zhifan Jiang, Yueming Jin, Smriti Joshi, Abdolrahim Kadkhodamohammadi, Reda Abdellah Kamraoui, Inha Kang, Junghwa Kang, Davood Karimi, April Khademi, Muhammad Irfan Khan, Suleiman A. Khan, Rishab Khantwal, Kwang-Ju Kim, Timothy Kline, Satoshi Kondo, Elina Kontio, Adrian Krenzer, Artem Kroviakov, Hugo Kuijf, Satyadwyoom Kumar, Francesco La Rosa, Abhi Lad, Doohee Lee, Minho Lee, Chiara Lena, Hao Li, Ling Li, Xingyu Li, Fuyuan Liao, Kuanlun Liao, Arlindo Limede Oliveira, Chaonan Lin, Shan Lin, Akis Linardos, Marius George Linguraru, Han Liu, Tao Liu, Di Liu, Yanling Liu, João Lourenço-Silva, Jingpei Lu, Jiangshan Lu, Imanol Luengo, Christina B. Lund, Huan Minh Luu, Yi Lv, Uzay Macar, Leon Maechler, Sina Mansour L., Kenji Marshall, Moona Mazher, Richard McKinley, Alfonso Medela, Felix Meissen, Mingyuan Meng, Dylan Miller, Seyed Hossein Mirjahanmardi, Arnab Mishra, Samir Mitha, Hassan Mohy-ud-Din, Tony Chi Wing Mok, Gowtham Krishnan Murugesan, Enamundram Naga Karthik, Sahil Nalawade, Jakub Nalepa, Mohamed Naser, Ramin Nateghi, Hammad Naveed, Quang-Minh Nguyen, Cuong Nguyen Quoc, Brennan Nichyporuk, Bruno Oliveira, David Owen, Jimut Bahan Pal, Junwen Pan, Wentao Pan, Winnie Pang, Bogyu Park, Vivek Pawar, Kamlesh Pawar, Michael Peven, Lena Philipp, Tomasz Pieciak, Szymon Plotka, Marcel Plutat, Fattaneh Pourakpour, Domen Preložnik, Kumaradevan Punithakumar, Abdul Qayyum, Sandro Queirós, Arman Rahmim, Salar Razavi, Jintao Ren, Mina Rezaei, Jonathan Adam Rico, ZunHyan Rieu, Markus Rink, Johannes Roth, Yusely Ruiz-Gonzalez, Numan Saeed, Anindo Saha, Mostafa Salem, Ricardo Sanchez-Matilla, Kurt Schilling, Wei Shao, Zhiqiang Shen, Ruize Shi, Pengcheng Shi, Daniel Sobotka, Théodore Soulier, Bella Specktor Fadida, Danail Stoyanov, Timothy Sum Hon Mun, Xiaowu Sun, Rong Tao, Franz Thaler, Antoine Théberge, Felix Thielke, Helena Torres, Kareem A. Wahid, Jiacheng Wang, Yifei Wang, Wei Wang, Xiong Wang, Jianhui Wen, Ning Wen, Marek Wodzinski, Ye Wu, Fangfang Xia, Tianqi Xiang, Chen Xiaofei, Lizhan Xu, Tingting Xue, Yuxuan Yang, Lin Yang, Kai Yao, Huifeng Yao, Amirsaeed Yazdani, Michael Yip, Hwanseung Yoo, Fereshteh Yousefirizi, Shunkai Yu, Lei Yu, Jonathan Zamora, Ramy Ashraf Zeineldin, Dewen Zeng, Jianpeng Zhang, Bokai Zhang, Jiapeng Zhang, Fan Zhang, Huahong Zhang, Zhongchen Zhao, Zixuan Zhao, Jiachen Zhao, Can Zhao, Qingshuo Zheng, Yuheng Zhi, Ziqi Zhou, Baosheng Zou, Klaus Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein

Of these, 84% were based on standard architectures.

Benchmarking

Labeling instructions matter in biomedical image analysis

no code implementations20 Jul 2022 Tim Rädsch, Annika Reinke, Vivienn Weru, Minu D. Tizabi, Nicholas Schreck, A. Emre Kavur, Bünyamin Pekdemir, Tobias Roß, Annette Kopp-Schneider, Lena Maier-Hein

Here, we present the first systematic study of labeling instructions and their impact on annotation quality in the field.

Metrics reloaded: Recommendations for image analysis validation

1 code implementation3 Jun 2022 Lena Maier-Hein, Annika Reinke, Patrick Godau, Minu D. Tizabi, Florian Buettner, Evangelia Christodoulou, Ben Glocker, Fabian Isensee, Jens Kleesiek, Michal Kozubek, Mauricio Reyes, Michael A. Riegler, Manuel Wiesenfarth, A. Emre Kavur, Carole H. Sudre, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, Tim Rädsch, Laura Acion, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew Blaschko, M. Jorge Cardoso, Veronika Cheplygina, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Florian Kofler, Annette Kopp-Schneider, Anna Kreshuk, Tahsin Kurc, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Nasir Rajpoot, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben van Calster, Gaël Varoquaux, Paul F. Jäger

The framework was developed in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint - a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output.

Instance Segmentation object-detection +2

Ten years of image analysis and machine learning competitions in dementia

no code implementations15 Dec 2021 Esther E. Bron, Stefan Klein, Annika Reinke, Janne M. Papma, Lena Maier-Hein, Daniel C. Alexander, Neil P. Oxtoby

Key for increasing impact in this way are larger testing data sizes, which could be reached by sharing algorithms rather than data to exploit data that cannot be shared.

BIG-bench Machine Learning

Robust deep learning-based semantic organ segmentation in hyperspectral images

1 code implementation9 Nov 2021 Silvia Seidlitz, Jan Sellner, Jan Odenthal, Berkin Özdemir, Alexander Studier-Fischer, Samuel Knödler, Leonardo Ayala, Tim J. Adler, Hannes G. Kenngott, Minu Tizabi, Martin Wagner, Felix Nickel, Beat P. Müller-Stich, Lena Maier-Hein

To address this gap in the literature, we are investigating the following research questions based on hyperspectral imaging (HSI) data of pigs acquired in an open surgery setting: (1) What is an adequate representation of HSI data for neural network-based fully automated organ segmentation, especially with respect to the spatial granularity of the data (pixels vs. superpixels vs. patches vs. full images)?

Image Segmentation Organ Segmentation +4

Task Fingerprinting for Meta Learning in Biomedical Image Analysis

no code implementations8 Jul 2021 Patrick Godau, Lena Maier-Hein

Task fingerprinting could thus become an important tool for meta learning in SDS and other fields of biomedical image analysis.

Meta-Learning

Video-rate multispectral imaging in laparoscopic surgery: First-in-human application

no code implementations28 May 2021 Leonardo Ayala, Sebastian Wirkert, Anant Vemuri, Tim Adler, Silvia Seidlitz, Sebastian Pirmann, Christina Engels, Dogu Teber, Lena Maier-Hein

Multispectral and hyperspectral imaging (MSI/HSI) can provide clinically relevant information on morphological and functional tissue properties.

Semantic segmentation of multispectral photoacoustic images using deep learning

no code implementations20 May 2021 Melanie Schellenberg, Kris Dreher, Niklas Holzwarth, Fabian Isensee, Annika Reinke, Nicholas Schreck, Alexander Seitel, Minu D. Tizabi, Lena Maier-Hein, Janek Gröhl

Due to the intuitive representation of high-dimensional information, such a preprocessing algorithm could be a valuable means to facilitate the clinical translation of photoacoustic imaging.

Segmentation Semantic Segmentation +1

The Federated Tumor Segmentation (FeTS) Challenge

2 code implementations12 May 2021 Sarthak Pati, Ujjwal Baid, Maximilian Zenk, Brandon Edwards, Micah Sheller, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Jason Martin, Shadi Albarqouni, Yong Chen, Russell Taki Shinohara, Annika Reinke, David Zimmerer, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Rivka R. Colen, Aikaterini Kotrotsou, Daniel Marcus, Mikhail Milchenko, Arash Nazer, Hassan Fathallah-Shaykh, Roland Wiest, Andras Jakab, Marc-Andre Weber, Abhishek Mahajan, Lena Maier-Hein, Jens Kleesiek, Bjoern Menze, Klaus Maier-Hein, Spyridon Bakas

The goals of the FeTS challenge are directly represented by the two included tasks: 1) the identification of the optimal weight aggregation approach towards the training of a consensus model that has gained knowledge via federated learning from multiple geographically distinct institutions, while their data are always retained within each institution, and 2) the federated evaluation of the generalizability of brain tumor segmentation models "in the wild", i. e. on data from institutional distributions that were not part of the training datasets.

Brain Tumor Segmentation Federated Learning +2

Common Limitations of Image Processing Metrics: A Picture Story

1 code implementation12 Apr 2021 Annika Reinke, Minu D. Tizabi, Carole H. Sudre, Matthias Eisenmann, Tim Rädsch, Michael Baumgartner, Laura Acion, Michela Antonelli, Tal Arbel, Spyridon Bakas, Peter Bankhead, Arriel Benis, Matthew Blaschko, Florian Buettner, M. Jorge Cardoso, Jianxu Chen, Veronika Cheplygina, Evangelia Christodoulou, Beth Cimini, Gary S. Collins, Sandy Engelhardt, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Fred Hamprecht, Daniel A. Hashimoto, Doreen Heckmann-Nötzel, Peter Hirsch, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, A. Emre Kavur, Hannes Kenngott, Jens Kleesiek, Andreas Kleppe, Sven Kohler, Florian Kofler, Annette Kopp-Schneider, Thijs Kooi, Michal Kozubek, Anna Kreshuk, Tahsin Kurc, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern Menze, David Moher, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, M. Alican Noyan, Jens Petersen, Gorkem Polat, Susanne M. Rafelski, Nasir Rajpoot, Mauricio Reyes, Nicola Rieke, Michael Riegler, Hassan Rivaz, Julio Saez-Rodriguez, Clara I. Sánchez, Julien Schroeter, Anindo Saha, M. Alper Selver, Lalith Sharan, Shravya Shetty, Maarten van Smeden, Bram Stieltjes, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul Jäger, Lena Maier-Hein

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation.

Instance Segmentation object-detection +2

SERV-CT: A disparity dataset from CT for validation of endoscopic 3D reconstruction

1 code implementation22 Dec 2020 P. J. "Eddie'' Edwards, Dimitris Psychogyios, Stefanie Speidel, Lena Maier-Hein, Danail Stoyanov

The SERV-CT dataset provides an easy to use stereoscopic validation for surgical applications with smooth reference disparities and depths with coverage over the majority of the endoscopic images.

3D Reconstruction Anatomy

Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks

no code implementations15 Dec 2020 Darya Trofimova, Tim Adler, Lisa Kausch, Lynton Ardizzone, Klaus Maier-Hein, Ulrich Köthe, Carsten Rother, Lena Maier-Hein

One example is the registration of 2D X-ray images with preoperative three-dimensional computed tomography (CT) images in intraoperative surgical guidance systems.

Computed Tomography (CT) Image Registration

Tattoo tomography: Freehand 3D photoacoustic image reconstruction with an optical pattern

no code implementations10 Nov 2020 Niklas Holzwarth, Melanie Schellenberg, Janek Gröhl, Kris Dreher, Jan-Hinrich Nölke, Alexander Seitel, Minu D. Tizabi, Beat P. Müller-Stich, Lena Maier-Hein

Methods: In this paper, we present a novel approach to 3D reconstruction of PAT data (Tattoo tomography) that does not require an external tracking system and can smoothly be integrated into clinical workflows.

3D Reconstruction Image Reconstruction

Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging

no code implementations10 Nov 2020 Jan-Hinrich Nölke, Tim Adler, Janek Gröhl, Thomas Kirchner, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Lena Maier-Hein

Multispectral photoacoustic imaging (PAI) is an emerging imaging modality which enables the recovery of functional tissue parameters such as blood oxygenation.

Uncertainty Quantification

Deep learning for biomedical photoacoustic imaging: A review

no code implementations5 Nov 2020 Janek Gröhl, Melanie Schellenberg, Kris Dreher, Lena Maier-Hein

Photoacoustic imaging (PAI) is a promising emerging imaging modality that enables spatially resolved imaging of optical tissue properties up to several centimeters deep in tissue, creating the potential for numerous exciting clinical applications.

Image Reconstruction Translation

Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks

no code implementations8 Mar 2019 Tim J. Adler, Lynton Ardizzone, Anant Vemuri, Leonardo Ayala, Janek Gröhl, Thomas Kirchner, Sebastian Wirkert, Jakob Kruse, Carsten Rother, Ullrich Köthe, Lena Maier-Hein

Assessment of the specific hardware used in conjunction with such algorithms, however, has not properly addressed the possibility that the problem may be ill-posed.

2017 Robotic Instrument Segmentation Challenge

3 code implementations18 Feb 2019 Max Allan, Alex Shvets, Thomas Kurmann, Zichen Zhang, Rahul Duggal, Yun-Hsuan Su, Nicola Rieke, Iro Laina, Niveditha Kalavakonda, Sebastian Bodenstedt, Luis Herrera, Wenqi Li, Vladimir Iglovikov, Huoling Luo, Jian Yang, Danail Stoyanov, Lena Maier-Hein, Stefanie Speidel, Mahdi Azizian

In mainstream computer vision and machine learning, public datasets such as ImageNet, COCO and KITTI have helped drive enormous improvements by enabling researchers to understand the strengths and limitations of different algorithms via performance comparison.

Benchmarking Person Re-Identification +2

Estimation of blood oxygenation with learned spectral decoloring for quantitative photoacoustic imaging (LSD-qPAI)

no code implementations15 Feb 2019 Janek Gröhl, Thomas Kirchner, Tim Adler, Lena Maier-Hein

In this work, we tackle the challenge by employing learned spectral decoloring for quantitative photoacoustic imaging (LSD-qPAI) to obtain quantitative estimates for blood oxygenation.

Analyzing Inverse Problems with Invertible Neural Networks

2 code implementations ICLR 2019 Lynton Ardizzone, Jakob Kruse, Sebastian Wirkert, Daniel Rahner, Eric W. Pellegrini, Ralf S. Klessen, Lena Maier-Hein, Carsten Rother, Ullrich Köthe

Often, the forward process from parameter- to measurement-space is a well-defined function, whereas the inverse problem is ambiguous: one measurement may map to multiple different sets of parameters.

Endoscopic Depth Measurement and Super-Spectral-Resolution Imaging

no code implementations19 Jun 2017 Jianyu Lin, Neil T. Clancy, Yang Hu, Ji Qi, Taran Tatla, Danail Stoyanov, Lena Maier-Hein, Daniel S. Elson

Intra-operative measurements of tissue shape and multi/ hyperspectral information have the potential to provide surgical guidance and decision making support.

Decision Making Optical Flow Estimation

Context encoding enables machine learning-based quantitative photoacoustics

no code implementations12 Jun 2017 Thomas Kirchner, Janek Gröhl, Lena Maier-Hein

Real-time monitoring of functional tissue parameters, such as local blood oxygenation, based on optical imaging could provide groundbreaking advances in the diagnosis and interventional therapy of various diseases.

BIG-bench Machine Learning

Clickstream analysis for crowd-based object segmentation with confidence

no code implementations25 Nov 2016 Eric Heim, Alexander Seitel, Jonas Andrulis, Fabian Isensee, Christian Stock, Tobias Ross, Lena Maier-Hein

Using a total of 29, 000 crowd annotations performed on publicly available data of different object classes, we show that (1) our method is highly accurate in estimating the segmentation quality based on clickstream data, (2) outperforms state-of-the-art methods for merging multiple annotations.

Image Segmentation Object +2

The HCI Stereo Metrics: Geometry-Aware Performance Analysis of Stereo Algorithms

no code implementations ICCV 2015 Katrin Honauer, Lena Maier-Hein, Daniel Kondermann

We show that the RMS is of limited expressiveness for algorithm selection and introduce the HCI Stereo Metrics.

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