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Recent advancements in biomedical image analysis have been significantly driven by the Segment Anything Model (SAM).
Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists’ detection of pulmonary nodules
Junji Shiraishi, Shigehiko Katsuragawa, Junpei Ikezoe, Tsuneo Matsumoto, Takeshi Kobayashi, Ken-ichi Komatsu, Mitate Matsui, Hiroshi Fujita, Yoshie Kodera, and Kunio Doi · 2000
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Image segmentation using deformable models
Chenyang Xu, Dzung L Pham, and Jerry L Prince · 2000
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Ridge-based vessel segmentation in color images of the retina
Joes Staal, Michael D Abràmoff, Meindert Niemeijer, Max A Viergever, and Bram Van Ginneken · 2004
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Active volume models for medical image segmentation
Tian Shen, Hongsheng Li, and Xiaolei Huang · 2010
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A hybrid region growing algorithm for medical image segmentation
D Muhammad Noorul Mubarak, M Mohamed Sathik, S Zulaikha Beevi, and K Revathy · 2012
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The cancer imaging archive (tcia): maintaining and operating a public information repository
Kenneth Clark, Bruce Vendt, Kirk Smith, John Freymann, Justin Kirby, Paul Koppel, Stephen Moore, Stanley Phillips, David Maffitt, Michael Pringle, et al · 2013
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Evaluation of prostate segmentation algorithms for mri: The promise12 challenge
Geert Litjens, Robert Toth, Wendy van de Ven, Caroline Hoeks, Sjoerd Kerkstra, Bram van Ginneken, Graham Vincent, Gwenael Guillard, Neil Birbeck, Jindang Zhang, Robin Strand, Filip Malmberg, Yangming Ou, Christos Davatzikos, Matthias Kirschner, Florian Jung, Jing Yuan, Wu Qiu, Qinquan Gao, Philip “Eddie” Edwards, Bianca Maan, Ferdinand van der Heijden, Soumya Ghose, Jhimli Mitra, Jason Dowling, Dean Barratt, Henkjan Huisman, and Anant Madabhushi · 2014
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The multimodal brain tumor image segmentation benchmark (brats)
Bjoern H Menze, Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, et al · 2014
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A new 2.5 d representation for lymph node detection using random sets of deep convolutional neural network observations
Holger R Roth, Le Lu, Ari Seff, Kevin M Cherry, Joanne Hoffman, Shijun Wang, Jiamin Liu, Evrim Turkbey, and Ronald M Summers · 2014
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Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the vessel12 study
Rina D Rudyanto, Sjoerd Kerkstra, Eva M Van Rikxoort, Catalin Fetita, Pierre-Yves Brillet, Christophe Lefevre, Wenzhe Xue, Xiangjun Zhu, Jianming Liang, Ilkay Öksüz, et al · 2014
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Nci-isbi 2013 challenge: Automated segmentation of prostate structures
N Bloch, A Madabhushi, H Huisman, J Freymann, J Kirby, M Grauer, A Enquobahrie, C Jaffe, L Clarke, and K Farahani · 2015
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Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge
B Landman, Z Xu, J Igelsias, M Styner, T Langerak, and A Klein · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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A new 2.5 d representation for lymph node detection in ct
H. Roth, L. Lu, A. Seff, K. M. Cherry, J. Hoffman, S. Wang, J. Liu, E. Turkbey, and R. M. Summers · 2015
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Deeporgan: Multi-level deep convolutional networks for automated pancreas segmentation
Holger R Roth, Le Lu, Amal Farag, Hoo-Chang Shin, Jiamin Liu, Evrim B Turkbey, and Ronald M Summers · 2015
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A stochastic polygons model for glandular structures in colon histology images
Korsuk Sirinukunwattana, David R. J. Snead, and Nasir M. Rajpoot · 2015
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3d u-net: learning dense volumetric segmentation from sparse annotation
Özgün Çiçek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger · 2016
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Data from pancreas-ct. the cancer imaging archive
Holger R Roth, Amal Farag, E Turkbey, Le Lu, Jiamin Liu, and Ronald M Summers · 2016
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Gland segmentation in colon histology images: The glas challenge contest, 2016
Korsuk Sirinukunwattana, Josien P. W. Pluim, Hao Chen, Xiaojuan Qi, Pheng-Ann Heng, Yun Bo Guo, Li Yang Wang, Bogdan J. Matuszewski, Elia Bruni, Urko Sanchez, Anton Böhm, Olaf Ronneberger, Bassem Ben Cheikh, Daniel Racoceanu, Philipp Kainz, Michael Pfeiffer, Martin Urschler, David R. J. Snead, and Nasir M. Rajpoot · 2016
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Segmentation labels and radiomic features for the pre-operative scans of the tcga-gbm collection (2017)
S Bakas, H Akbari, A Sotiras, M Bilello, M Rozycki, J Kirby, J Freymann, K Farahani, and C Davatzikos · 2017
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Segmentation labels and radiomic features for the pre-operative scans of the tcga-lgg collection
Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin Kirby, John Freymann, Keyvan Farahani, and Christos Davatzikos · 2017
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Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features
Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin S Kirby, John B Freymann, Keyvan Farahani, and Christos Davatzikos · 2017
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A multi-scale 3d otsu thresholding algorithm for medical image segmentation
Yuncong Feng, Haiying Zhao, Xiongfei Li, Xiaoli Zhang, and Hongpeng Li · 2017
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A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism
Mojtaba Masoudi, Hamid-Reza Pourreza, Mahdi Saadatmand-Tarzjan, Noushin Eftekhari, Fateme Shafiee Zargar, and Masoud Pezeshki Rad · 2018
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Automated design of deep learning methods for biomedical image segmentation
Fabian Isensee, Paul F Jäger, Simon AA Kohl, Jens Petersen, and Klaus H Maier-Hein · 2019
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CHAOS - Combined (CT-MR) Healthy Abdominal Organ Segmentation Challenge Data, Apr. 2019
Ali Emre Kavur, M. Alper Selver, Oğuz Dicle, Mustafa Barış, and N. Sinem Gezer · 2019
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Deep learning for segmentation using an open large-scale dataset in 2d echocardiography
Sarah Leclerc, Erik Smistad, Joao Pedrosa, Andreas Østvik, Frederic Cervenansky, Florian Espinosa, Torvald Espeland, Erik Andreas Rye Berg, Pierre-Marc Jodoin, Thomas Grenier, et al · 2019
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Siim-acr pneumothorax segmentation, 2019
Anna Zawacki, Carol Wu, George Shih, Julia Elliott, Mikhail Fomitchev, Mohannad Hussain, Paras Lakhani, Phil Culliton, and Shunxing Bao · 2019
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Dataset of breast ultrasound images
Walid Al-Dhabyani, Mohammed Gomaa, Hussien Khaled, and Aly Fahmy · 2020
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Can ai help in screening viral and covid-19 pneumonia?
Muhammad EH Chowdhury, Tawsifur Rahman, Amith Khandakar, Rashid Mazhar, Muhammad Abdul Kadir, Zaid Bin Mahbub, Khandakar Reajul Islam, Muhammad Salman Khan, Atif Iqbal, Nasser Al Emadi, et al · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Comparison of semi-automatic and deep learning based automatic methods for liver segmentation in living liver transplant donors
A. Emre Kavur, Naciye Sinem Gezer, Mustafa Barış, Yusuf Şahin, Savaş Özkan, Bora Baydar, Ulaş Yüksel, Çağlar Kılıkçıer, Şahin Olut, Gözde Bozdağı Akar, Gözde Ünal, Oğuz Dicle, and M. Alper Selver · 2020
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Mosmeddata: Chest ct scans with covid-19 related findings dataset
Sergey P Morozov, AE Andreychenko, NA Pavlov, AV Vladzymyrskyy, NV Ledikhova, VA Gombolevskiy, Ivan A Blokhin, PB Gelezhe, AV Gonchar, and V Yu Chernina · 2020
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Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
José Ignacio Orlando, Huazhu Fu, João Barbosa Breda, Karel Van Keer, Deepti R Bathula, Andrés Diaz-Pinto, Ruogu Fang, Pheng-Ann Heng, Jeyoung Kim, JoonHo Lee, et al · 2020
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Improving realism in patient-specific abdominal ultrasound simulation using cyclegans
Santiago Vitale, José Ignacio Orlando, Emmanuel Iarussi, and Ignacio Larrabide · 2020
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Sau-net: Efficient 3d spine mri segmentation using inter-slice attention
Yichi Zhang, Lin Yuan, Yujia Wang, and Jicong Zhang · 2020
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Chest x-ray pneumothorax segmentation using u-net with efficientnet and resnet architectures
Ayat Abedalla, Malak Abdullah, Mahmoud Al-Ayyoub, and Elhadj Benkhelifa · 2021
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Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
Sharib Ali, Mariia Dmitrieva, Noha Ghatwary, Sophia Bano, Gorkem Polat, Alptekin Temizel, Adrian Krenzer, Amar Hekalo, Yun Bo Guo, Bogdan Matuszewski, et al · 2021
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Polypgen: A multi-center polyp detection and segmentation dataset for generalisability assessment
Sharib Ali, Debesh Jha, Noha Ghatwary, Stefano Realdon, Renato Cannizzaro, Osama E Salem, Dominique Lamarque, Christian Daul, Michael A Riegler, Kim V Anonsen, et al · 2021
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Overview of the hecktor challenge at miccai 2021: automatic head and neck tumor segmentation and outcome prediction in pet/ct images
Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Catherine Cheze Le Rest, Hesham Elhalawani, Mario Jreige, John O Prior, Martin Vallières, Dimitris Visvikis, Mathieu Hatt, et al · 2021
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A deep learning approach to segmentation of nasopharyngeal carcinoma using computed tomography
Xiaoyu Bai, Yan Hu, Guanzhong Gong, Yong Yin, and Yong Xia · 2021
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Ujjwal Baid, Satyam Ghodasara, Suyash Mohan, Michel Bilello, Evan Calabrese, Errol Colak, Keyvan Farahani, Jayashree Kalpathy-Cramer, Felipe C Kitamura, Sarthak Pati, et al · 2021
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Multi-centre, multi-vendor and multi-disease cardiac segmentation: the m&ms challenge
Victor M Campello, Polyxeni Gkontra, Cristian Izquierdo, Carlos Martin-Isla, Alireza Sojoudi, Peter M Full, Klaus Maier-Hein, Yao Zhang, Zhiqiang He, Jun Ma, et al · 2021
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Transunet: Transformers make strong encoders for medical image segmentation
Jieneng Chen, Yongyi Lu, Qihang Yu, Xiangde Luo, Ehsan Adeli, Yan Wang, Le Lu, Alan L Yuille, and Yuyin Zhou · 2021
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Covid-19 infection map generation and detection from chest x-ray images
Aysen Degerli, Mete Ahishali, Mehmet Yamac, Serkan Kiranyaz, Muhammad EH Chowdhury, Khalid Hameed, Tahir Hamid, Rashid Mazhar, and Moncef Gabbouj · 2021
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Automated lung segmentation from ct images of normal and covid-19 pneumonia patients
Faeze Gholamiankhah, Samaneh Mostafapour, Nouraddin Abdi Goushbolagh, Seyedjafar Shojaerazavi, Parvaneh Layegh, Seyyed Mohammad Tabatabaei, and Hossein Arabi · 2021
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Domain-specific language model pretraining for biomedical natural language processing
Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, and Hoifung Poon · 2021
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Deep learning based detection and segmentation of covid-19 & pneumonia on chest x-ray image
Md Jahid Hasan, Md Shahin Alom, and Md Shikhar Ali · 2021
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nnu-net: a self-configuring method for deep learning-based biomedical image segmentation
Fabian Isensee, Paul F Jaeger, Simon AA Kohl, Jens Petersen, and Klaus H Maier-Hein · 2021
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CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation
A. Emre Kavur, N. Sinem Gezer, Mustafa Barış, Sinem Aslan, Pierre-Henri Conze, Vladimir Groza, Duc Duy Pham, Soumick Chatterjee, Philipp Ernst, Savaş Özkan, Bora Baydar, Dmitry Lachinov, Shuo Han, Josef Pauli, Fabian Isensee, Matthias Perkonigg, Rachana Sathish, Ronnie Rajan, Debdoot Sheet, Gurbandurdy Dovletov, Oliver Speck, Andreas Nürnberger, Klaus H. Maier-Hein, Gözde Bozdağı Akar, Gözde Ünal, Oğuz Dicle, and M. Alper Selver · 2021
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Exploring the effect of image enhancement techniques on covid-19 detection using chest x-ray images
Tawsifur Rahman, Amith Khandakar, Yazan Qiblawey, Anas Tahir, Serkan Kiranyaz, Saad Bin Abul Kashem, Mohammad Tariqul Islam, Somaya Al Maadeed, Susu M Zughaier, Muhammad Salman Khan, et al · 2021
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Covid-19 infection localization and severity grading from chest x-ray images
Anas M Tahir, Muhammad EH Chowdhury, Amith Khandakar, Tawsifur Rahman, Yazan Qiblawey, Uzair Khurshid, Serkan Kiranyaz, Nabil Ibtehaz, M Sohel Rahman, Somaya Al-Maadeed, et al · 2021
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Transbts: Multimodal brain tumor segmentation using transformer
Wenxuan Wang, Chen Chen, Meng Ding, Hong Yu, Sen Zha, and Jiangyun Li · 2021
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A hybrid network for automatic hepatocellular carcinoma segmentation in h&e-stained whole slide images
Xiyue Wang, Yuqi Fang, Sen Yang, Delong Zhu, Minghui Wang, Jing Zhang, Kai-yu Tong, and Xiao Han · 2021
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Cotr: Efficiently bridging cnn and transformer for 3d medical image segmentation
Yutong Xie, Jianpeng Zhang, Chunhua Shen, and Yong Xia · 2021
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nnformer: Interleaved transformer for volumetric segmentation
Hong-Yu Zhou, Jiansen Guo, Yinghao Zhang, Lequan Yu, Liansheng Wang, and Yizhou Yu · 2021
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Sharib Ali, Noha Ghatwary, Debesh Jha, Ece Isik-Polat, Gorkem Polat, Chen Yang, Wuyang Li, Adrian Galdran, Miguel-Angel González Ballester, Vajira Thambawita, et al · 2022
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Connected-segnets: A deep learning model for breast tumor segmentation from x-ray images
Mohammad Alkhaleefah, Tan-Hsu Tan, Chuan-Hsun Chang, Tzu-Chuan Wang, Shang-Chih Ma, Lena Chang, and Yang-Lang Chang · 2022
Cited alongside, same era.
The medical segmentation decathlon
Michela Antonelli, Annika Reinke, Spyridon Bakas, Keyvan Farahani, Annette Kopp-Schneider, Bennett A Landman, Geert Litjens, Bjoern Menze, Olaf Ronneberger, Ronald M Summers, et al · 2022
Cited alongside, same era.
Medical image segmentation review: The success of u-net
Reza Azad, Ehsan Khodapanah Aghdam, Amelie Rauland, Yiwei Jia, Atlas Haddadi Avval, Afshin Bozorgpour, Sanaz Karimijafarbigloo, Joseph Paul Cohen, Ehsan Adeli, and Dorit Merhof · 2022
Cited alongside, same era.
Osegnet: Operational segmentation network for covid-19 detection using chest x-ray images
Aysen Degerli, Serkan Kiranyaz, Muhammad E. H. Chowdhury, and Moncef Gabbouj · 2022
Cited alongside, same era.
Thoracic lymph node segmentation in ct imaging via lymph node station stratification and size encoding
Dazhou Guo, Jia Ge, Ke Yan, Puyang Wang, Zhuotun Zhu, Dandan Zheng, Xian-Sheng Hua, Le Lu, Tsung-Ying Ho, Xianghua Ye, et al · 2022
Segment anything, 2023
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick · 2023
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The asnr-miccai brain tumor segmentation (brats) challenge 2023: Intracranial meningioma
Dominic LaBella, Maruf Adewole, Michelle Alonso-Basanta, Talissa Altes, Syed Muhammad Anwar, Ujjwal Baid, Timothy Bergquist, Radhika Bhalerao, Sully Chen, Verena Chung, et al · 2023
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Iamsam: Image-based analysis of molecular signatures using the segment-anything model
Dongjoo Lee, Jeongbin Park, Seungho Cook, seong-jin Yoo, Daeseung Lee, and Hongyoon Choi · 2023
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3d UX-net: A large kernel volumetric convnet modernizing hierarchical transformer for medical image segmentation
Ho Hin Lee, Shunxing Bao, Yuankai Huo, and Bennett A. Landman · 2023
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Scaling up 3d kernels with bayesian frequency re-parameterization for medical image segmentation
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Cited alongside, same era.
Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images
Ali Hatamizadeh, Vishwesh Nath, Yucheng Tang, Dong Yang, Holger R Roth, and Daguang Xu · 2022
Cited alongside, same era.
Unetr: Transformers for 3d medical image segmentation
Ali Hatamizadeh, Yucheng Tang, Vishwesh Nath, Dong Yang, Andriy Myronenko, Bennett Landman, Holger R Roth, and Daguang Xu · 2022
Cited alongside, same era.
Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
Cited alongside, same era.
Isles 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset
Moritz R Hernandez Petzsche, Ezequiel de la Rosa, Uta Hanning, Roland Wiest, Waldo Valenzuela, Mauricio Reyes, Maria Meyer, Sook-Lei Liew, Florian Kofler, Ivan Ezhov, et al · 2022
Cited alongside, same era.
Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation
Yuanfeng Ji, Haotian Bai, Jie Yang, Chongjian Ge, Ye Zhu, Ruimao Zhang, Zhen Li, Lingyan Zhang, Wanling Ma, Xiang Wan, et al · 2022
Cited alongside, same era.
Ho Hin Lee, Shunxing Bao, Yuankai Huo, and Bennett A Landman · 2022
Cited alongside, same era.
Automatic lung segmentation in chest x-ray images using improved u-net
Wufeng Liu, Jiaxin Luo, Yan Yang, Wenlian Wang, Junkui Deng, and Liang Yu · 2022
Cited alongside, same era.
Ho Hin Lee, Quan Liu, Shunxing Bao, Qi Yang, Xin Yu, Leon Y Cai, Thomas Li, Yuankai Huo, Xenofon Koutsoukos, and Bennett A Landman · 2023
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Ho Hin Lee, Quan Liu, Qi Yang, Xin Yu, Shunxing Bao, Yuankai Huo, and Bennett A Landman · 2023
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Medlsam: Localize and segment anything model for 3d medical images
Wenhui Lei, Xu Wei, Xiaofan Zhang, Kang Li, and Shaoting Zhang · 2023
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Auto-prompting sam for mobile friendly 3d medical image segmentation
Chengyin Li, Prashant Khanduri, Yao Qiang, Rafi Ibn Sultan, Indrin Chetty, and Dongxiao Zhu · 2023
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Segment anything model for semi-supervised medical image segmentation via selecting reliable pseudo-labels
Ning Li, Lianjin Xiong, Wei Qiu, Yudong Pan, Yiqian Luo, and Yangsong Zhang · 2023
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Xiangyu Li, Gongning Luo, Kuanquan Wang, Hongyu Wang, Shuo Li, Jun Liu, Xinjie Liang, Jie Jiang, Zhenghao Song, Chunyue Zheng, et al · 2023
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Samscore: A semantic structural similarity metric for image translation evaluation
Yunxiang Li, Meixu Chen, Wenxuan Yang, Kai Wang, Jun Ma, Alan C Bovik, and You Zhang · 2023
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Polyp-sam: Transfer sam for polyp segmentation
Yuheng Li, Mingzhe Hu, and Xiaofeng Yang · 2023
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Xian Lin, Yangyang Xiang, Li Zhang, Xin Yang, Zengqiang Yan, and Li Yu · 2023
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Clip-driven universal model for organ segmentation and tumor detection
Jie Liu, Yixiao Zhang, Jie-Neng Chen, Junfei Xiao, Yongyi Lu, Bennett A Landman, Yixuan Yuan, Alan Yuille, Yucheng Tang, and Zongwei Zhou · 2023
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Samm (segment any medical model): A 3d slicer integration to sam
Yihao Liu, Jiaming Zhang, Zhangcong She, Amir Kheradmand, and Mehran Armand · 2023
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Segment anything in medical images
Jun Ma and Bo Wang · 2023
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Christian Mattjie, Luis Vinicius de Moura, Rafaela Cappelari Ravazio, Lucas Silveira Kupssinskü, Otávio Parraga, Marcelo Mussi Delucis, and Rodrigo Coelho Barros · 2023
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Segment anything model for medical image analysis: an experimental study
Maciej A Mazurowski, Haoyu Dong, Hanxue Gu, Jichen Yang, Nicholas Konz, and Yixin Zhang · 2023
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Ahmed W Moawad, Anastasia Janas, Ujjwal Baid, Divya Ramakrishnan, Leon Jekel, Kiril Krantchev, Harrison Moy, Rachit Saluja, Klara Osenberg, Klara Wilms, et al · 2023
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Brain extraction comparing segment anything model (sam) and fsl brain extraction tool
Sovesh Mohapatra, Advait Gosai, and Gottfried Schlaug · 2023
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Adaptivesam: Towards efficient tuning of sam for surgical scene segmentation
Jay N Paranjape, Nithin Gopalakrishnan Nair, Shameema Sikder, S Swaroop Vedula, and Vishal M Patel · 2023
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Han-seg: The head and neck organ-at-risk ct and mr segmentation dataset
Gašper Podobnik, Primož Strojan, Primož Peterlin, Bulat Ibragimov, and Tomaž Vrtovec · 2023
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Florian Putz, Johanna Grigo, Thomas Weissmann, Philipp Schubert, Daniel Hoefler, Ahmed Gomaa, Hassen Ben Tkhayat, Amr Hagag, Sebastian Lettmaier, Benjamin Frey, et al · 2023
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Zhongxi Qiu, Yan Hu, Heng Li, and Jiang Liu · 2023
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Exploring sam ablations for enhancing medical segmentation in radiology and pathology
Amin Ranem, Niklas Babendererde, Moritz Fuchs, and Anirban Mukhopadhyay · 2023
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Sam. md: Zero-shot medical image segmentation capabilities of the segment anything model
Saikat Roy, Tassilo Wald, Gregor Koehler, Maximilian R Rokuss, Nico Disch, Julius Holzschuh, David Zimmerer, and Klaus H Maier-Hein · 2023
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3d mru-net: A novel mobile residual u-net deep learning model for spine segmentation using computed tomography images
Muhammad Usman Saeed, Wang Bin, Jinfang Sheng, Ghulam Ali, and Aqsa Dastgir · 2023
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Artificial intelligence and radiologists at prostate cancer detection in mri—the pi-cai challenge
Anindo Saha, Joeran Bosma, Jasper Twilt, Bram van Ginneken, Derya Yakar, Mattijs Elschot, Jeroen Veltman, Jurgen Fütterer, Maarten de Rooij, et al · 2023
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Tomosam: a 3d slicer extension using sam for tomography segmentation
Federico Semeraro, Alexandre Quintart, Sergio Fraile Izquierdo, and Joseph C Ferguson · 2023
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Autosam: Adapting sam to medical images by overloading the prompt encoder
Tal Shaharabany, Aviad Dahan, Raja Giryes, and Lior Wolf · 2023
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Temporally-extended prompts optimization for sam in interactive medical image segmentation
Chuyun Shen, Wenhao Li, Ya Zhang, and Xiangfeng Wang · 2023
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Generalist vision foundation models for medical imaging: A case study of segment anything model on zero-shot medical segmentation
Peilun Shi, Jianing Qiu, Sai Mu Dalike Abaxi, Hao Wei, Frank P-W Lo, and Wu Yuan · 2023
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Xiaoyu Shi, Shurong Chai, Yinhao Li, Jingliang Cheng, Jie Bai, Guohua Zhao, and Yen-Wei Chen · 2023
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Dongik Shin, Beomsuk Kim, and Seungjun Baek · 2023
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Self-supervised learning with application for infant cerebellum segmentation and analysis
Yue Sun, Limei Wang, Kun Gao, Shihui Ying, Weili Lin, Kathryn L Humphreys, Gang Li, Sijie Niu, Mingxia Liu, and Li Wang · 2023
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Pathasst: Redefining pathology through generative foundation ai assistant for pathology
Yuxuan Sun, Chenglu Zhu, Sunyi Zheng, Kai Zhang, Zhongyi Shui, Xiaoxuan Yu, Yizhi Zhao, Honglin Li, Yunlong Zhang, Ruojia Zhao, et al · 2023
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The fully convolutional transformer for medical image segmentation
Athanasios Tragakis, Chaitanya Kaul, Roderick Murray-Smith, and Dirk Husmeier · 2023
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A combined u-net and multi-class support vector machine learning models for diabetic retinopathy macula edema segmentation and classification dme
Pamula Udayaraju, K Sreerama Murthy, P Jeyanthi, Bh VS Raju, T Rajasri, and N Ramadevi · 2023
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A deep learning based dual encoder–decoder framework for anatomical structure segmentation in chest x-ray images
Ihsan Ullah, Farman Ali, Babar Shah, Shaker El-Sappagh, Tamer Abuhmed, and Sang Hyun Park · 2023
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Sam meets robotic surgery: An empirical study on generalization, robustness and adaptation
An Wang, Mobarakol Islam, Mengya Xu, Yang Zhang, and Hongliang Ren · 2023
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Gazesam: What you see is what you segment
Bin Wang, Armstrong Aboah, Zheyuan Zhang, and Ulas Bagci · 2023
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Sammed: A medical image annotation framework based on large vision model
Chenglong Wang, Dexuan Li, Sucheng Wang, Chengxiu Zhang, Yida Wang, Yun Liu, and Guang Yang · 2023
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Application of artificial intelligence methods in carotid artery segmentation: a review
Yu Wang and Yudong Yao · 2023
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TotalSegmentator: Robust segmentation of 104 anatomic structures in CT images
Jakob Wasserthal, Hanns-Christian Breit, Manfred T. Meyer, Maurice Pradella, Daniel Hinck, Alexander W. Sauter, Tobias Heye, Daniel T. Boll, Joshy Cyriac, Shan Yang, Michael Bach, and Martin Segeroth · 2023
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Medical sam adapter: Adapting segment anything model for medical image segmentation
Junde Wu, Rao Fu, Huihui Fang, Yuanpei Liu, Zhaowei Wang, Yanwu Xu, Yueming Jin, and Tal Arbel · 2023
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Self-prompting large vision models for few-shot medical image segmentation, 2023
Qi Wu, Yuyao Zhang, and Marawan Elbatel · 2023
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Piclick: Picking the desired mask in click-based interactive segmentation
Cilin Yan, Haochen Wang, Jie Liu, Xiaolong Jiang, Yao Hu, Xu Tang, Guoliang Kang, and Efstratios Gavves · 2023
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False negative/positive control for sam on noisy medical images
Xing Yao, Han Liu, Dewei Hu, Daiwei Lu, Ange Lou, Hao Li, Ruining Deng, Gabriel Arenas, Baris Oguz, Nadav Schwartz, et al · 2023
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Sam-path: A segment anything model for semantic segmentation in digital pathology
Jingwei Zhang, Ke Ma, Saarthak Kapse, Joel Saltz, Maria Vakalopoulou, Prateek Prasanna, and Dimitris Samaras · 2023
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Customized segment anything model for medical image segmentation
Kaidong Zhang and Dong Liu · 2023
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How segment anything model (sam) boost medical image segmentation?
Yichi Zhang and Rushi Jiao · 2023
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Self-sampling meta sam: Enhancing few-shot medical image segmentation with meta-learning
Yiming Zhang, Tianang Leng, Kun Han, and Xiaohui Xie · 2023
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Input augmentation with sam: Boosting medical image segmentation with segmentation foundation model
Yizhe Zhang, Tao Zhou, Peixian Liang, and Danny Z Chen · 2023
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Yizhe Zhang, Tao Zhou, Shuo Wang, Ye Wu, Pengfei Gu, and Danny Z Chen · 2023
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Tao Zhou, Yizhe Zhang, Yi Zhou, Ye Wu, and Chen Gong · 2023
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Segment everything everywhere all at once
Xueyan Zou, Jianwei Yang, Hao Zhang, Feng Li, Linjie Li, Jianfeng Gao, and Yong Jae Lee · 2023
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