Texture and Mathematical Morphology for Hot-Spot Detection in Whole Slide Images of Meningiomas and Oligodendrogliomas. - Zaneta Swiderska; Tomasz Markiewicz; Bartlomiej Grala; Wojciech Kozlowski (CAIP (2), 2015)

Hot-spot selection and evaluation methods for whole slice images of meningiomas and oligodendrogliomas. - Zaneta Swiderska; Tomasz Markiewicz; Bartlomiej Grala; Janina Slodkowska (EMBC, 2015)

Hourglass Shapes in Rank Grey-Level Hit-or-miss Transform for Membrane Segmentation in HER2/neu Images. - Marek Wdowiak; Tomasz Markiewicz; Stanislaw Osowski; Zaneta Swiderska; Janusz Patera; Wojciech Kozlowski (ISMM, 2015)

Texture Analysis to Trophoblast and Villi Detection in Placenta Histological Images. - Zaneta Swiderska-Chadaj; Tomasz Markiewicz; Robert Koktysz; Wojciech Kozlowski (ITIB (2), 2016)

A Deep Learning Pipeline to Delineate Proliferative Areas of Intracranial Tumors in Digital Slides. - Zaneta Swiderska-Chadaj; Tomasz Markiewicz; Bartlomiej Grala; Malgorzata Lorent; Arkadiusz Gertych (MIUA, 2017)

Semantic Segmentation of Colon Glands in Inflammatory Bowel Disease Biopsies. - Zhaoxuan Ma; Zaneta Swiderska-Chadaj; Nathan Ing; Hootan Salemi; Dermot P. B. McGovern; Beatrice S. Knudsen; Arkadiusz Gertych (ITIB, 2018)

Image processing methods for the structural detection and gradation of placental villi. - Zaneta Swiderska-Chadaj; Tomasz Markiewicz; Robert Koktysz; Szczepan Cierniak (Comput. Biol. Medicine, 2018)

Contextual Classification of Tumor Growth Patterns in Digital Histology Slides. - Zaneta Swiderska-Chadaj; Zhaoxuan Ma; Nathan Ing; Tomasz Markiewicz; Malgorzata Lorent; Szczepan Cierniak; Ann E. Walts; Beatrice S. Knudsen; Arkadiusz Gertych (ITIB, 2019)

Learning to detect lymphocytes in immunohistochemistry with deep learning. - Zaneta Swiderska-Chadaj; Hans Pinckaers; Mart van Rijthoven; Maschenka Balkenhol; Margarita Melnikova; Oscar Geessink; Quirine Manson; Mark Sherman 003; António Polónia; Jeremy Parry; Mustapha Abubakar; Geert Litjens 001; et al. (Medical Image Anal., 2019)

A deep learning approach to assess the predominant tumor growth pattern in whole-slide images of lung adenocarcinoma. - Zaneta Swiderska-Chadaj; Karolina Nurzynska; Bartlomiej Grala; Katrien Grunberg; Lieke van der Woude; Monika Looijen-Salamon; Ann E. Walts; Tomasz Markiewicz; Francesco Ciompi; Arkadiusz Gertych (Digital Pathology, 2020)

Predicting MYC translocation in HE specimens of diffuse large B-cell lymphoma through deep learning. - Zaneta Swiderska-Chadaj; Konnie M. Hebeda; Michiel van den Brand; Geert Litjens 001 (Digital Pathology, 2020)

Automatic generation of graphical game assets using GAN. - Rafal Karp; Zaneta Swiderska-Chadaj (ICCTA, 2021)

A U-Net based framework to quantify glomerulosclerosis in digitized PAS and H&E stained human tissues. - Jaime Gallego; Zaneta Swiderska-Chadaj; Tomasz Markiewicz; Michifumi Yamashita; M. Alejandra Gabaldon; Arkadiusz Gertych (Comput. Medical Imaging Graph., 2021)

HE-to-PAS histological stain conversion by GAN in renal pathology. - Mateusz Lysik; Zaneta Swiderska-Chadaj; Tomasz Markiewicz; Tomasz Les; Szczepan Cierniak; Malgorzata Lorent (IJCNN, 2022)

Efficient annotation bootstrapping for cell identification in follicular lymphoma. - Adam Krawczyk; Aleksandra Maria Osowska-Kurczab; Slawomir Pakulo; Wojciech Kotlowski; Zaneta Swiderska-Chadaj (Comput. Methods Programs Biomed., 2025)