Domain adaptation strategies for cancer-independent detection of lymph node metastases

Authors: Bándi, Péter, Balkenhol, Maschenka, van Dijk, Marcory, van Ginneken, Bram, van der Laak, Jeroen, Litjens, Geert

Subject Terms: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning

Access URL: http://arxiv.org/abs/2207.06193

Automated Scoring of Nuclear Pleomorphism Spectrum with Pathologist-level Performance in Breast Cancer

Authors: Mercan, Caner, Balkenhol, Maschenka, Salgado, Roberto, Sherman, Mark, Vielh, Philippe, Vreuls, Willem, Polonia, Antonio, Horlings, Hugo M., Weichert, Wilko, Carter, Jodi M., Bult, Peter, Christgen, Matthias, Denkert, Carsten, van de Vijver, Koen, van der Laak, Jeroen, Ciompi, Francesco

Subject Terms: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition

Access URL: http://arxiv.org/abs/2012.04974

HookNet: multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images

Authors: van Rijthoven, Mart, Balkenhol, Maschenka, Siliņa, Karina, van der Laak, Jeroen, Ciompi, Francesco

Subject Terms: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning

Access URL: http://arxiv.org/abs/2006.12230

Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists

Authors: Bulten, Wouter, Balkenhol, Maschenka, Belinga, Jean-Joël Awoumou, Brilhante, Américo, Çakır, Aslı, Farré, Xavier, Geronatsiou, Katerina, Molinié, Vincent, Pereira, Guilherme, Roy, Paromita, Saile, Günter, Salles, Paulo, Schaafsma, Ewout, Tschui, Joëlle, Vos, Anne-Marie, van Boven, Hester, Vink, Robert, van der Laak, Jeroen, de Kaa, Christina Hulsbergen-van, Litjens, Geert

Source: Modern Pathology, Available online 5 August 2020

Subject Terms: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Quantitative Biology - Quantitative Methods

Access URL: http://arxiv.org/abs/2002.04500

Continual learning strategies for cancer-independent detection of lymph node metastases

Authors: Bándi, Péter, Balkenhol, Maschenka, van Dijk, Marcory, Kok, Michel, van Ginneken, Bram, van der Laak, Jeroen, Litjens, Geert

Source: In Medical Image Analysis April 2023 85

Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks

Authors: Tellez, David, Balkenhol, Maschenka, Otte-Holler, Irene, van de Loo, Rob, Vogels, Rob, Bult, Peter, Wauters, Carla, Vreuls, Willem, Mol, Suzanne, Karssemeijer, Nico, Litjens, Geert, van der Laak, Jeroen, Ciompi, Francesco

Subject Terms: Computer Science - Computer Vision and Pattern Recognition

Access URL: http://arxiv.org/abs/1808.05896

Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images

Authors: Bejnordi, Babak Ehteshami, Zuidhof, Guido, Balkenhol, Maschenka, Hermsen, Meyke, Bult, Peter, van Ginneken, Bram, Karssemeijer, Nico, Litjens, Geert, van der Laak, Jeroen

Subject Terms: Computer Science - Computer Vision and Pattern Recognition

Access URL: http://arxiv.org/abs/1705.03678

Interobserver variability in the assessment of stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative invasive breast carcinoma influences the association with pathological complete response: the IVITA study

Authors: Van Bockstal, Mieke R., François, Aline, Altinay, Serdar, Arnould, Laurent, Balkenhol, Maschenka, Broeckx, Glenn, Burguès, Octavio, Colpaert, Cecile, Dedeurwaerdere, Franceska, Dessauvagie, Benjamin, Duwel, Valérie, Floris, Giuseppe, Fox, Stephen, Gerosa, Clara, Hastir, Delfyne, Jaffer, Shabnam, Kurpershoek, Eline, Lacroix-Triki, Magali, Laka, Andoni, Lambein, Kathleen, MacGrogan, Gaëtan Marie, Marchiò, Caterina, Martin Martinez, Maria-Dolores, Nofech-Mozes, Sharon, Peeters, Dieter, Ravarino, Alberto, Reisenbichler, Emily, Resetkova, Erika, Sanati, Souzan, Schelfhout, Anne-Marie, Schelfhout, Vera, Shaaban, Abeer, Sinke, Renata, Stanciu-Pop, Claudia M., van Deurzen, Carolien H.M., Van de Vijver, Koen K., Van Rompuy, Anne-Sophie, Vincent-Salomon, Anne, Wen, Hannah Y., Wong, Serena, Bouzin, Caroline, Galant, Christine

Source: In Modern Pathology December 2021 34(12):2130-2140

Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics

Authors: Balkenhol, Maschenka CA., Ciompi, Francesco, Świderska-Chadaj, Żaneta, van de Loo, Rob, Intezar, Milad, Otte-Höller, Irene, Geijs, Daan, Lotz, Johannes, Weiss, Nick, de Bel, Thomas, Litjens, Geert, Bult, Peter, van der Laak, Jeroen AWM.

Source: In The Breast April 2021 56:78-87

HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images

Authors: van Rijthoven, Mart, Balkenhol, Maschenka, Siliņa, Karina, van der Laak, Jeroen, Ciompi, Francesco

Source: In Medical Image Analysis February 2021 68

Histological subtypes in triple negative breast cancer are associated with specific information on survival

Authors: Balkenhol, Maschenka C.A., Vreuls, Willem, Wauters, Carla A.P., Mol, Suzanne J.J., van der Laak, Jeroen A.W.M., Bult, Peter

Source: In Annals of Diagnostic Pathology June 2020 46

Learning to detect lymphocytes in immunohistochemistry with deep learning

Authors: Swiderska-Chadaj, Zaneta, Pinckaers, Hans, van Rijthoven, Mart, Balkenhol, Maschenka, Melnikova, Margarita, Geessink, Oscar, Manson, Quirine, Sherman, Mark, Polonia, Antonio, Parry, Jeremy, Abubakar, Mustapha, Litjens, Geert, van der Laak, Jeroen, Ciompi, Francesco

Source: In Medical Image Analysis December 2019 58

Deep learning assisted mitotic counting for breast cancer

Authors: Balkenhol, Maschenka C.A., Tellez, David, Vreuls, Willem, Clahsen, Pieter C., Pinckaers, Hans, Ciompi, Francesco, Bult, Peter, van der Laak, Jeroen A.W.M.

Source: In Laboratory Investigation November 2019 99(11):1596-1606

Few-shot weakly supervised detection and retrieval in histopathology whole-slide images
Medical Imaging 2021: Digital Pathology

Authors: van Rijthoven, Mart, Balkenhol, Maschenka, Atzori, Manfredo, Bult, Peter, van der Laak, Jeroen, Ciompi, Francesco

Source: Proceedings of SPIE, the International Society for Optical Engineering. 11603:116030N-116030N-7

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCCN900028640&indx=1&recIds=ETOCCN900028640

Evaluation Criteria for Chromosome Instability Detection by FISH to Predict Malignant Progression in Premalignant Glottic Laryngeal Lesions.

Authors: Bergshoeff, Verona E.^1,2 (AUTHOR) maschenka.balkenhol@radboudumc.nl, Balkenhol, Maschenka C. A.^1,3 (AUTHOR) m.chenault@mumc.nl, Haesevoets, Annick⁴ (AUTHOR) annick.haesevoets@maastrichtuniversity.nl, Ruland, Andrea⁴ (AUTHOR) andrea.ruland@mumc.nl, Chenault, Michelene N.^1,5 (AUTHOR) r.nelissen@antoniusziekenhuis.nl, Nelissen, Rik C.^1,6 (AUTHOR) bernd.kremer@mumc.nl, Peutz, Carine J.⁴ (AUTHOR) carine.peutz@mumc.nl, Clarijs, Ruud⁷ (AUTHOR) r.clarijs@zuyderland.nl, Van der Laak, Jeroen A. W. M.³ (AUTHOR), Takes, Robert P.⁸ (AUTHOR) robert.takes@radboudumc.nl, Van den Brekel, Michiel W.⁹ (AUTHOR) m.vd.brekel@nki.nl, Van Velthuysen, Marie-Louise F.¹⁰ (AUTHOR) m.vanvelthuysen@erasmusmc.nl, Ramaekers, Frans C. S.¹¹ (AUTHOR) f.ramaekers@maastrichtuniversity.nl, Kremer, Bernd¹ (AUTHOR), Speel, Ernst-Jan M.⁴ (AUTHOR) ernstjan.speel@mumc.nl

Source: Cancers. Jul2022, Vol. 14 Issue 13, pN.PAG-N.PAG. 15p.

Subject Terms: *HEAD & neck cancer diagnosis, *DISEASE progression, *RISK assessment, *CHROMOSOME abnormalities, *LARYNGEAL diseases, *FLUORESCENCE in situ hybridization, *HISTOLOGICAL techniques, *DESCRIPTIVE statistics, *TUMOR markers, *ODDS ratio, *RECEIVER operating characteristic curves, *SENSITIVITY & specificity (Statistics), *DISEASE complications

From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge

Authors: Bandi, Peter, Geessink, Oscar, Manson, Quirine, Van Dijk, Marcory, Balkenhol, Maschenka, Hermsen, Meyke, Ehteshami Bejnordi, Babak, Lee, Byungjae, Paeng, Kyunghyun, Zhong, Aoxiao, Li, Quanzheng, Zanjani, Farhad Ghazvinian, Zinger, Svitlana, Fukuta, Keisuke, Komura, Daisuke, Ovtcharov, Vlado, Cheng, Shenghua, Zeng, Shaoqun, Thagaard, Jeppe, Dahl, Anders B., Lin, Huangjing, Chen, Hao, Jacobsson, Ludwig, Hedlund, Martin, cetin, Melih, Halici, Eren, Jackson, Hunter, Chen, Richard, Both, Fabian, Franke, Jorg, Kusters-Vandevelde, Heidi, Vreuls, Willem, Bult, Peter, van Ginneken, Bram, van der Laak, Jeroen, Litjens, Geert

Source: IEEE transactions on medical imaging. 38(2):550-560

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCvdc_100075936161.0x000001&indx=1&recIds=ETOCvdc_100075936161.0x000001

Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer

Authors: Balkenhol, Maschenka C. A., Bult, Peter, Tellez, David, Vreuls, Willem, Clahsen, Pieter C., Ciompi, Francesco, van der Laak, Jeroen A. W. M.

Source: Cellular oncology. 42(4):555-569

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCvdc_100130350992.0x000001&indx=1&recIds=ETOCvdc_100130350992.0x000001

Sonographic Phenotypes of Molecular Subtypes of Invasive Ductal Cancer in Automated 3-D Breast Ultrasound

Authors: van Zelst, Jan C.M. ^∗, Balkenhol, Maschenka, Tan, Tao ^∗, Rutten, Matthieu, Imhof-Tas, Mechli ^∗, Bult, Peter, Karssemeijer, Nico ^∗, Mann, Ritse M. ^∗

Source: In Ultrasound in Medicine & Biology September 2017 43(9):1820-1828

Automated mitotic spindle hotspot counts are highly associated with clinical outcomes in systemically untreated early-stage triple-negative breast cancer.

Authors: Leon-Ferre, Roberto A., Carter, Jodi M., Zahrieh, David, Sinnwell, Jason P., Salgado, Roberto, Suman, Vera J., Hillman, David W., Boughey, Judy C., Kalari, Krishna R., Couch, Fergus J., Ingle, James N., Balkenhol, Maschenka, Ciompi, Francesco, van der Laak, Jeroen, Goetz, Matthew P.

Source: NPJ Breast Cancer; 3/29/2024, Vol. 10 Issue 1, p1-10, 10p

PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.

Authors: Aswolinskiy, Witali, Munari, Enrico, Horlings, Hugo M., Mulder, Lennart, Bogina, Giuseppe, Sanders, Joyce, Liu, Yat-Hee, van den Belt-Dusebout, Alexandra W., Tessier, Leslie, Balkenhol, Maschenka, Stegeman, Michelle, Hoven, Jeffrey, Wesseling, Jelle, van der Laak, Jeroen, Lips, Esther H., Ciompi, Francesco

Source: Breast Cancer Research; 11/13/2023, Vol. 25 Issue 1, p1-15, 15p

Subject Terms: NEOADJUVANT chemotherapy, CANCER chemotherapy, DEEP learning, BREAST cancer, RECEIVER operating characteristic curves, RECTAL cancer