Zobrazeno 1 - 10
of 591
pro vyhledávání: '"Van Der Laak, Jeroen"'
Autor:
Jurgas, Artur, Wodzinski, Marek, D'Amato, Marina, van der Laak, Jeroen, Atzori, Manfredo, Müller, Henning
Publikováno v:
Scientific Reports volume 14, Article number: 17847 (2024)
The problem of artifacts in whole slide image acquisition, prevalent in both clinical workflows and research-oriented settings, necessitates human intervention and re-scanning. Overcoming this challenge requires developing quality control algorithms,
Externí odkaz:
http://arxiv.org/abs/2406.11538
Vision Transformers are at the heart of the current surge of interest in foundation models for histopathology. They process images by breaking them into smaller patches following a regular grid, regardless of their content. Yet, not all parts of an i
Externí odkaz:
http://arxiv.org/abs/2404.18152
Deep learning algorithms, often critiqued for their 'black box' nature, traditionally fall short in providing the necessary transparency for trusted clinical use. This challenge is particularly evident when such models are deployed in local hospitals
Externí odkaz:
http://arxiv.org/abs/2404.07208
Vision Transformers (ViTs) have ushered in a new era in computer vision, showcasing unparalleled performance in many challenging tasks. However, their practical deployment in computational pathology has largely been constrained by the sheer size of w
Externí odkaz:
http://arxiv.org/abs/2312.12619
Autor:
Jiao, Yiping, van der Laak, Jeroen, Albarqouni, Shadi, Li, Zhang, Tan, Tao, Bhalerao, Abhir, Ma, Jiabo, Sun, Jiamei, Pocock, Johnathan, Pluim, Josien P. W., Koohbanani, Navid Alemi, Bashir, Raja Muhammad Saad, Raza, Shan E Ahmed, Liu, Sibo, Graham, Simon, Wetstein, Suzanne, Khurram, Syed Ali, Watson, Thomas, Rajpoot, Nasir, Veta, Mitko, Ciompi, Francesco
We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzen (China). The competition required participants to automatically assess the number of lymphocytes, in particular T-cells,
Externí odkaz:
http://arxiv.org/abs/2301.06304
Autor:
Bándi, Péter, Balkenhol, Maschenka, van Dijk, Marcory, van Ginneken, Bram, van der Laak, Jeroen, Litjens, Geert
Recently, large, high-quality public datasets have led to the development of convolutional neural networks that can detect lymph node metastases of breast cancer at the level of expert pathologists. Many cancers, regardless of the site of origin, can
Externí odkaz:
http://arxiv.org/abs/2207.06193
Autor:
Faryna, Khrystyna, Tessier, Leslie, Retamero, Juan, Bonthu, Saikiran, Samanta, Pranab, Singhal, Nitin, Kammerer-Jacquet, Solene-Florence, Radulescu, Camelia, Agosti, Vittorio, Collin, Alexandre, Farre´, Xavier, Fontugne, Jacqueline, Grobholz, Rainer, Hoogland, Agnes Marije, Moreira Leite, Katia Ramos, Oktay, Murat, Polonia, Antonio, Roy, Paromita, Salles, Paulo Guilherme, van der Kwast, Theodorus H., van Ipenburg, Jolique, van der Laak, Jeroen, Litjens, Geert
Publikováno v:
In Modern Pathology November 2024 37(11)
Autor:
Bokhorst, John-Melle, Nagtegaal, Iris D., Fraggetta, Filippo, Vatrano, Simona, Mesker, Wilma, Vieth, Michael, van der Laak, Jeroen, Ciompi, Francesco
Artificial Intelligence (AI) can potentially support histopathologists in the diagnosis of a broad spectrum of cancer types. In colorectal cancer (CRC), AI can alleviate the laborious task of characterization and reporting on resected biopsies, inclu
Externí odkaz:
http://arxiv.org/abs/2109.07892
Purpose: In digital histopathology, virtual multi-staining is important for diagnosis and biomarker research. Additionally, it provides accurate ground-truth for various deep-learning tasks. Virtual multi-staining can be obtained using different stai
Externí odkaz:
http://arxiv.org/abs/2106.13150
Publikováno v:
In Medical Image Analysis April 2024 93