- Elizabeth A. Krupinski:
Translating computational innovations into reality: focus on the users! Digital and Computational Pathology 2023 - Xu Lei, Fahad Parvez Mahdi, Ze Jin, Hao Sun, Yoshiyuki Noguchi, Masayuki Murata, Kenji Suzuki:
Generating simulated fluorescence images for enhancing proteins from optical microscopy images of cells using massive-training artificial neural networks. Digital and Computational Pathology 2023 - Haoju Leng, Ruining Deng, Zuhayr Asad, R. Michael Womick, Haichun Yang, Lipeng Wan, Yuankai Huo:
An accelerated pipeline for multi-label renal pathology image segmentation at the whole slide image level. Digital and Computational Pathology 2023 - Peize Li, Ruining Deng, Yuankai Huo:
An end-to-end pipeline for 3D slide-wise multi-stain renal pathology registration. Digital and Computational Pathology 2023 - Peng Lu, Karolyn A. Oetjen, Daniel L. J. Thorek:
Interpretable graph convolutional network enables triple negative breast cancer detection in imaging mass cytometry. Digital and Computational Pathology 2023 - Brendon Lutnick, Nicholas J. Lucarelli, Pinaki Sarder:
Generative modeling of histology tissue reduces human annotation effort for segmentation model development. Digital and Computational Pathology 2023 - Ling Ma, Jeremy Sherey, Doreen Palsgrove, Baowei Fei:
Conditional generative adversarial network (cGAN) for synthesis of digital histologic images from hyperspectral images. Digital and Computational Pathology 2023 - Seyed Hossein Mirjahanmardi, Melanie Dawe, Anthony Fyles, Wei Shi, Dimitri Androutsos, Fei-Fei Liu, Susan Done, April Khademi:
Ki67 proliferation index quantification using silver standard masks. Digital and Computational Pathology 2023 - Shayan Monabbati, Sirvan Khalighi, Pingfu Fu, Sylvia Asa, Anant Madabhushi:
A pathomic study for risk stratification and unraveling molecular associations of different histologic subtypes of papillary thyroid cancer. Digital and Computational Pathology 2023 - Raghava Vinaykanth Mushunuri, Matthias Choschzick, Ulf-Dietrich Braumann, Juergen Hess:
An ensemble approach for histopathological classification of vulvar cancer. Digital and Computational Pathology 2023 - Kristen Ong, Xuezhu Cai, Vasant Marur, Veronica Soloveva, Uwe Mueller, Antong Chen:
Deep learning-based rapid macrophage cell detection and localization in high-content microscopy screening. Digital and Computational Pathology 2023 - Milda Poceviciute, Gabriel Eilertsen, Claes Lundström:
Spatial uncertainty aggregation for false negatives detection in breast cancer metastases segmentation. Digital and Computational Pathology 2023 - Monika Pytlarz, K. Wojnicki, P. Pilanc, B. Kaminska, Alessandro Crimi:
Automated glioma multiclass tumor classification. Digital and Computational Pathology 2023 - Taranpreet Rai, Ioannis Papanikolaou, N. Dave, A. Morisi, B. Bacci, Spencer Angus Thomas, R. M. La Ragione, Kevin Wells:
Investigating the potential of untrained convolutional layers and pruning in computational pathology. Digital and Computational Pathology 2023 - Vishwesh Ramanathan, Wenchao Han, Dina Bassiouny, Eileen Rakovitch, Anne L. Martel:
Ink removal in whole slide images using hallucinated data. Digital and Computational Pathology 2023 - Armand Rathgeb, Ling Ma, Minh Tran, Baowei Fei:
Extended depth of field imaging for mosaic hyperspectral images. Digital and Computational Pathology 2023 - Lucas W. Remedios, Shunxing Bao, Cailey I. Kerley, Leon Y. Cai, François Rheault, Ruining Deng, Can Cui, Sophie Chiron, Ken S. Lau, Joseph T. Roland, Mary K. Washington, Lori A. Coburn, Keith T. Wilson, Yuankai Huo, Bennett A. Landman:
Predicting Crohn's disease severity in the colon using mixed cell nucleus density from pseudo labels. Digital and Computational Pathology 2023 - Hyung S. Roh, David J. Irwin, Mónica Muñoz López, Maria Mercedes Iñiguez de Onzoño Martin, Ranjit Ittyerah, Sydney Lim, Madigan L. Bedard, John L. Robinson, Theresa Schuck, Emilio Artacho-Pérula, María del Mar Arroyo Jiménez, Maria del Pilar Marcos Rabal, Francisco Javier Molina Romero, Sandra Cebada Sánchez, José Carlos Delgado González, Carlos de la Rosa-Prieto, Marta Córcoles Parada, Edward B. Lee, Daniel T. Ohm, Laura E. M. Wisse, David A. Wolk, James C. Gee, Ricardo Insausti, Paul A. Yushkevich, Min Chen:
Integrating color deconvolution thresholding and weakly supervised learning for automated segmentation of neurofibrillary tangle and neuropil threads. Digital and Computational Pathology 2023 - Adam Saunders, Sajal Dash, Aristeidis Tsaris, Hong-Jun Yoon:
A comparison of histopathology imaging comprehension algorithms based on multiple instance learning. Digital and Computational Pathology 2023 - Daan N. Schouten, Geert J. S. Litjens:
PythoStitcher: an iterative approach for stitching digitized tissue fragments into full resolution whole-mount reconstructions. Digital and Computational Pathology 2023 - Sourya Sengupta, Michael John Fanous, Hua Li, Mark A. Anastasio:
Semi-supervised contrastive learning for white blood cell segmentation from label-free quantitative phase imaging. Digital and Computational Pathology 2023 - Aman Shah, Amal Mehta, Michael Wang, Neil Neumann, Avideh Zakhor, Timothy McCalmont:
Deep learning segmentation of invasive melanoma. Digital and Computational Pathology 2023 - Benjamin Shickel, Nicholas J. Lucarelli, Adish Rao, Donghwan Yun, Kyung Chul Moon, Seung Seok Han, Pinaki Sarder:
Spatially aware transformer networks for contextual prediction of diabetic nephropathy progression from whole slide images. Digital and Computational Pathology 2023 - Jing Wei Tan, Khoa Tuan Nguyen, Kyoungbun Lee, Won-Ki Jeong:
Multi-scale contrastive learning with attention for histopathology image classification. Digital and Computational Pathology 2023 - Thomas E. Tavolara, Wei Chen, Wendy L. Frankel, Metin N. Gurcan, M. Khalid Khan Niazi:
Minimizing the intra-pathologist disagreement for tumor bud detection on H&E images using weakly supervised learning. Digital and Computational Pathology 2023 - Thomas E. Tavolara, Metin N. Gurcan, M. Khalid Khan Niazi:
The effects of sparsity induction methods on attention-based multiple instance learning applied to Camelyon16. Digital and Computational Pathology 2023 - Thomas E. Tavolara, M. Khalid Khan Niazi, Metin N. Gurcan:
Background detection affects downstream classification of Camelyon16 whole slide images. Digital and Computational Pathology 2023 - Thomas E. Tavolara, M. Khalid Khan Niazi, Metin N. Gurcan:
Simple patch-wise transformations serve as a mechanism for slide-level augmentation for multiple instance learning applications. Digital and Computational Pathology 2023 - Thomas E. Tavolara, M. Khalid Khan Niazi, David Jaye, Christopher Flowers, Lee Cooper, Metin N. Gurcan:
Deep learning to predict the proportion of positive cells in CMYC-stained tissue microarrays of diffuse large B-cell lymphoma. Digital and Computational Pathology 2023 - Leihui Tong, Yuan Wan:
Deep learning combined with ball scale transform for circulating tumor cell enumeration in digital pathology. Digital and Computational Pathology 2023
