Results 1 to 10 of about 345,506 (334)

A graph-transformer for whole slide image classification [PDF]

IEEE Transactions on Medical Imaging, 2022
Deep learning is a powerful tool for whole slide image (WSI) analysis. Typically, when performing supervised deep learning, a WSI is divided into small patches, trained and the outcomes are aggregated to estimate disease grade. However, patch-based methods introduce label noise during training by assuming that each patch is independent with the same ...
Yi Zheng, Rushin H. Gindra, Emily J. Green, Eric Burks, Margrit Betke, Jennifer Beane, Vijaya B. Kolachalama   +6 more
openalex   +4 more sources

A novel automatic annotation method for whole slide pathological images combined clustering and edge detection technique [PDF]

IET Image Processing
Pixel‐level labeling of regions of interest in an image is a key step in building a labeled training dataset for supervised deep learning networks of images.
Wei‐long Ding, Wan‐yin Liao, Xiao‐jie Zhu, Hong‐bo Zhu   +3 more
doaj   +2 more sources

Adaptive compression framework for giga-pixel whole slide images [PDF]

Nature Communications
Digital pathology generates gigapixel whole-slide images that require extensive storage, limiting scalability and increasing costs. Traditional compression methods apply uniform ratios, disregarding variations in diagnostic importance across regions ...
Jonghyun Lee, Lina Takemaru, D. M. Bappy, Ye Sul Jeong, Won-Ki Jeong, Derek Oldridge, Dokyoon Kim, Sangjeong Ahn, Sung Hak Lee   +8 more
doaj   +2 more sources

Multimodal analysis of whole slide images in colorectal cancer [PDF]

npj Digital Medicine
Multimodal models have enabled the integration of digital pathology, radiology, clinical information, and omics data to enhance Colorectal cancer (CRC) care.
Jitendra Jonnagaddala, Miljana Shulajkovska, Anton Gradišek, Toni Rose Jue, Qifeng Zhou, Yuzhi Guo, Jamil Mahmoud El Chayeb, Ruijiang Li, Jana Lipkova, Jakob Nikolas Kather, Junzhou Huang   +10 more
doaj   +2 more sources

An annotation-free whole-slide training approach to pathological classification of lung cancer types using deep learning

Nature Communications, 2021
Deep learning for digital pathology is hindered by the extremely high spatial resolution of whole slide images (WSIs), which requires researchers to adopt patch-based methods and laborious free-hand contouring.
Chi-Long Chen, Chi-Chung Chen, Wei-Hsiang Yu   +2 more
exaly   +2 more sources

Generating dermatopathology reports from gigapixel whole slide images with HistoGPT [PDF]

Nature Communications
Histopathology is the reference standard for diagnosing the presence and nature of many diseases, including cancer. However, analyzing tissue samples under a microscope and summarizing the findings in a comprehensive pathology report is time-consuming ...
Manuel Tran, Paul Schmidle, Ruifeng Ray Guo, Sophia J. Wagner, Valentin Koch, Valerio Lupperger, Brenna Novotny, Dennis H. Murphree, Heather D. Hardway, Marina D’Amato, Judith Lefkes, Daan J. Geijs, Annette Feuchtinger, Alexander Böhner, Robert Kaczmarczyk, Tilo Biedermann, Avital L. Amir, Antien L. Mooyaart, Francesco Ciompi, Geert Litjens, Chen Wang, Nneka I. Comfere, Kilian Eyerich, Stephan A. Braun, Carsten Marr, Tingying Peng   +25 more
doaj   +2 more sources

A deep learning model to predict RNA-Seq expression of tumours from whole slide images [PDF]

Nature Communications, 2020
Benoît Schmauch, Charlie Saillard, Julien Calderaro   +2 more
exaly   +2 more sources

Whole slide image data utilization informed by digital diagnosis patterns

Journal of Pathology Informatics, 2022
Context: Despite the benefits of digital pathology, data storage and management of digital whole slide images introduces new logistical and infrastructure challenges to traditionally analog pathology labs.
Kimberly Ashman, Huimin Zhuge, Erin Shanley, Sharon Fox, Shams Halat, Andrew Sholl, Brian Summa, J. Quincy Brown   +7 more
doaj   +1 more source

SlideJ: An ImageJ plugin for automated processing of whole slide images. [PDF]

PLoS ONE, 2017
The digital slide, or Whole Slide Image, is a digital image, acquired with specific scanners, that represents a complete tissue sample or cytological specimen at microscopic level. While Whole Slide image analysis is recognized among the most interesting
Vincenzo Della Mea, Giulia L Baroni, David Pilutti, Carla Di Loreto   +3 more
doaj   +1 more source

Scale-Aware Transformers for Diagnosing Melanocytic Lesions

IEEE Access, 2021
Diagnosing melanocytic lesions is one of the most challenging areas of pathology with extensive intra- and inter-observer variability. The gold standard for a diagnosis of invasive melanoma is the examination of histopathological whole slide skin biopsy ...
Wenjun Wu, Sachin Mehta, Shima Nofallah, Stevan Knezevich, Caitlin J. May, Oliver H. Chang, Joann G. Elmore, Linda G. Shapiro   +7 more
doaj   +1 more source