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ORCIDDigital and Computational Pathology 2023: San Diego, CA, USA
- John E. Tomaszewski, Aaron D. Ward:
Medical Imaging 2023: Digital and Computational Pathology, San Diego, CA, USA, February 19-23, 2023. SPIE Proceedings 12039, SPIE 2023, ISBN 9781510660472 - Front Matter: Volume 12471.
Automated Quantification of tissue biomarkers
- Olivia Krebs, Shobhit Agarwal, Pallavi Tiwari:
Self-supervised deep learning to predict molecular markers from routine histopathology slides for high-grade glioma tumors. - 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. - 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. - Chao-Hui Huang, Yoson Park, Jincheng Pang, Jadwiga R. Bienkowska:
Single-cell gene expression prediction using H&E images based on spatial transcriptomics.
Multi-Stain, multiplexed, and Multispectral imaging and Analysis I
- Wenchao Han, Alison M. Cheung, Vishwesh Ramanathan, Dan Wang, Kela Liu, Martin J. Yaffe, Anne L. Martel:
Identification of molecular cell type of breast cancer on digital histopathology images using deep learning and multiplexed fluorescence imaging. - Minh Ha Tran, Ofelia Gomez, Baowei Fei:
A video transformer network for thyroid cancer detection on hyperspectral histologic images. - Chang Bian, Tim Cootes, Martin Fergie:
A transformer-based computational approach for H&E to multiplexed immunohistochemistry stain translation. - Armand Rathgeb, Ling Ma, Minh Tran, Baowei Fei:
Extended depth of field imaging for mosaic hyperspectral images. - Can Cui, Shunxing Bao, Jia Li, Ruining Deng, Lucas W. Remedios, Zuhayr Asad, Sophie Chiron, Ken S. Lau, Yaohong Wang, Lori A. Coburn, Keith T. Wilson, Joseph T. Roland, Bennett A. Landman, Qi Liu, Yuankai Huo:
Influence of cell-type ratio on spatially resolved single-cell transcriptomes using the Tangram algorithm: based on implementation on single-cell and MxIF data.
Multi-Stain, multiplexed, and Multispectral imaging and Analysis II
- Shunxing Bao, Can Cui, Jia Li, Yucheng Tang, Ho Hin Lee, Ruining Deng, Lucas W. Remedios, Xin Yu, Qi Yang, Sophie Chiron, Nathan Heath Patterson, Ken S. Lau, Qi Liu, Joseph T. Roland, Lori A. Coburn, Keith T. Wilson, Bennett A. Landman, Yuankai Huo:
Topological-preserving membrane skeleton segmentation in multiplex immunofluorescence imaging. - Peng Lu, Karolyn A. Oetjen, Daniel L. J. Thorek:
Interpretable graph convolutional network enables triple negative breast cancer detection in imaging mass cytometry. - Tanwi Biswas, Hiroyuki Suzuki, Masahiro Ishikawa, Naoki Kobayashi, Takashi Obi:
Generation of RGB EVG stained image from hyperspectral H&E stained image using generative adversarial network (GAN). - 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. - Peize Li, Ruining Deng, Yuankai Huo:
An end-to-end pipeline for 3D slide-wise multi-stain renal pathology registration. - Samuel P. Border, Avi Rosenberg, Jarcy Zee, Richard M. Levenson, Kuang-Yu Jen, Pinaki Sarder, Farzad Fereidouni:
Improving quantification of renal fibrosis using deep-DUET.
Grading and Classification of Pathology Images I
- Brennan T. Flannery, Priti Lal, Michael D. Feldman, María Natalizio, Juan C. Santa-Rosario, Anant Madabhushi:
Biopsy and surgical specimen specific deep learning models for prostate cancer detection on digitized pathology images. - Alexander F. B. Carmichael, Johanna L. Baily, Aaron Reeves, Gabriela Ochoa, Annette S. Boerlage, George J. Gunn, Rosa Allshire, Deepayan Bhowmik:
Analysing hyperplasia in Atlantic salmon gills using empirical wavelets. - Trinh Thi Le Vuong, Jin Tae Kwak:
Quintet margin loss for an improved knowledge distillation in histopathology image analysis. - 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.
Grading and Classification of Pathology Images II
- 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. - 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. - Sena Korkut, Cihan Erkan, Selim Aksoy:
On the benefits of region of interest detection for whole slide image classification. - Thomas E. Tavolara, M. Khalid Khan Niazi, Metin N. Gurcan:
Background detection affects downstream classification of Camelyon16 whole slide images.
Segmentation of Cellular and tissue Structures
- 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. - 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. - Palak Dave, Yaroslav Kolinko, Hunter Morera, Kurtis Allen, Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton:
MIMO U-Net: efficient cell segmentation and counting in microscopy image sequences.
Wednesday morning Keynotes
- Elizabeth A. Krupinski:
Translating computational innovations into reality: focus on the users!
Computer-Aided Diagnosis, prognosis and predictive Analysis I
- Seyed M. M. Kahaki, Ian S. Hagemann, Kenny H. Cha, Christopher J. Trindade, Nicholas Petrick, Nicolas Kostelecky, Weijie Chen:
Weakly supervised deep learning for predicting the response to hormonal treatment of women with atypical endometrial hyperplasia: a feasibility study. - Germán Corredor, Can Koyuncu, Andrew Janowczyk, Paula Toro, Sepideh Azarianpour, James S. Lewis Jr., Anant Madabhushi:
Spatial connectivity of tumor and associated cells (SpaCell): a novel computational pathology biomarker. - Yufei Zhou, Can Koyuncu, Cristian Barrera, Germán Corredor, Xiangxue Wang, Cheng Lu, Anant Madabhushi:
Transformer as a spatially-aware multi-instance learning framework to predict the risk of death for early-stage non-small cell lung cancer. - Milda Poceviciute, Gabriel Eilertsen, Claes Lundström:
Spatial uncertainty aggregation for false negatives detection in breast cancer metastases segmentation.
Computer-Aided Diagnosis, prognosis and predictive Analysis II
- Roozbeh Bazargani, Wanwen Chen, Sadaf Sadeghian, Maryam Asadi, Jeffrey Boschman, Amirali Darbandsari, Ali Bashashati, Septimiu E. Salcudean:
A novel H&E color augmentation for domain invariance classification of unannotated histopathology prostate cancer images. - Vishwesh Ramanathan, Wenchao Han, Dina Bassiouny, Eileen Rakovitch, Anne L. Martel:
Ink removal in whole slide images using hallucinated data. - Naga Raju Gudhe, Mazen Sudah, Arto Mannermaa, Veli-Matti Kosma, Hamid Behravan:
Predicting cell type counts in whole slide histology images using evidential multi-task learning. - Jack Breen, Katie Allen, Kieran Zucker, Geoff Hall, Nicolas M. Orsi, Nishant Ravikumar:
Efficient subtyping of ovarian cancer histopathology whole slide images using active sampling in multiple instance learning. - Leihui Tong, Yuan Wan:
Deep learning combined with ball scale transform for circulating tumor cell enumeration in digital pathology.
Medical Applications
- Jonathan Folmsbee, Margaret Brandwein-Weber, Scott Doyle:
Combining multiple ground truth annotations for segmentation training for oral cavity cancer. - 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. - 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. - Jing Wei Tan, Khoa Tuan Nguyen, Kyoungbun Lee, Won-Ki Jeong:
Multi-scale contrastive learning with attention for histopathology image classification. - 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.
From cell Detection to whole-Slide imaging
- 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. - Daan N. Schouten, Geert J. S. Litjens:
PythoStitcher: an iterative approach for stitching digitized tissue fragments into full resolution whole-mount reconstructions. - 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. - Carlos Vega, Laura Quintana, Samuel Ortega, Himar Fabelo, Esther Sauras, Noèlia Gallardo, Daniel Mata Cano, Marylène Lejeune, Carlos López, Gustavo M. Callicó:
YOLOX-based framework for nuclei detection on whole-slide histopathological RGB and hyperspectral images.
Poster Session
- Jason Keighley, Marc de Kamps, Alexander I. Wright, Darren Treanor:
Digital pathology whole slide image compression with vector quantized variational autoencoders. - Areej Alsaafin, Morteza Babaie, Hamid R. Tizhoosh:
Deep modality association learning using histopathology images and immune cell sequencing data. - Ling Ma, Jeremy Sherey, Doreen Palsgrove, Baowei Fei:
Conditional generative adversarial network (cGAN) for synthesis of digital histologic images from hyperspectral images. - 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. - Alison M. Cheung, Hassan Besher, Dan Wang, Kela Liu, Yutaka Amemiya, Jianan Chen, Anne L. Martel, Arun Seth, Martin J. Yaffe:
Integrated image-processing and transcriptomic analysis of cancer-associated fibroblasts (CAFs) in breast cancer subtypes. - Michael H. Udin, Scott T. Doyle, Ciprian N. Ionita, Umesh C. Sharma, Saraswati Pokharel:
Automated identification of cardiomyocyte nuclei in H&E-stained heart tissue with CycleGAN. - Arian Arab, Victor Garcia, Shuyue Guan, Brandon D. Gallas, Berkman Sahiner, Nicholas Petrick, Weijie Chen:
Effect of color-normalization on deep learning segmentation models for tumor-infiltrating lymphocytes scoring using breast cancer histopathology images. - Monika Pytlarz, K. Wojnicki, P. Pilanc, B. Kaminska, Alessandro Crimi:
Automated glioma multiclass tumor classification. - Paras Goel, Saarthak Kapse, Prateek Prasanna:
Role of stain normalization in computational pathology: use case in metastatic tissue classification. - Laurin Herbsthofer, Barbara Ehall, Martina Tomberger, Barbara Prietl, Thomas R. Pieber, Pablo López-García:
Cell2Voxel: a novel, cell-based 3D tissue model from 2D multiplex tissue scans. - Cihan Erkan, Selim Aksoy:
Space-filling curves for modeling spatial context in transformer-based whole slide image classification. - Adam Saunders, Sajal Dash, Aristeidis Tsaris, Hong-Jun Yoon:
A comparison of histopathology imaging comprehension algorithms based on multiple instance learning. - Hooria Hajiyan, Mehran Ebrahimi:
Multi-scale local explanation approach for image analysis using model-agnostic Explainable Artificial Intelligence (XAI). - Santiago Castro, David Romo-Bucheli, Luis Guayacán, Fabio Martínez:
Fast detection and localization of mitosis using a semi-supervised deep representation. - Aman Shah, Amal Mehta, Michael Wang, Neil Neumann, Avideh Zakhor, Timothy McCalmont:
Deep learning segmentation of invasive melanoma. - Brendon Lutnick, Nicholas J. Lucarelli, Pinaki Sarder:
Generative modeling of histology tissue reduces human annotation effort for segmentation model development. - Brandon Ginley, Nicholas J. Lucarelli, Jarcy Zee, Sanjay Jain, Seung Seok Han, Luis Rodrigues, Michelle L. Wong, Kuang-Yu Jen, Pinaki Sarder:
Automated reference kidney histomorphometry using a panoptic segmentation neural network correlates to patient demographics and creatinine. - J. Arslan, Mehdi Ounissi, H. Luo, M. Lacroix, P. Dupré, P. Kumar, Arran Hodgkinson, S. Dandou, Romain M. Larive, C. Pignodel, L. Le Cam, Ovidiu Radulescu, Daniel Racoceanu:
Efficient 3D reconstruction of whole slide images in melanoma. - Gabriel Jimenez, Pablo Mas, Anuradha Kar, Julien Peyrache, Léa Ingrassia, Susana Boluda, Benoît Delatour, Lev Stimmer, Daniel Racoceanu:
A meta-graph approach for analyzing whole slide histopathological images of human brain tissue with Alzheimer's disease biomarkers. - Jingjing Zhao, Aidan Van Vleck, Yonatan Winetraub, Lin Du, Yong Han, Sumaira Aasi, Kavita Yang Sarin, Adam de la Zerda:
Multifocal optical metasurfaces for cellular-resolution optical coherence tomography for rapid slide-free histology of human brain and skin samples. - Zhimin Wang, Zong Fan, Lulu Sun, Yao Hao, Hiram A. Gay, Wade L. Thorstad, Xiaowei Wang, Hua Li:
Deep-supervised adversarial learning-based classification for digital histologic images.
Digital poster Session
- Hao Wu, Xinjian Chen, Weifang Zhu, Fei Shi, Dehui Xiang:
Enhanced pooling-convolution for pathological image multi-class segmentation. - Zhibang Zhou, Dehui Xiang, Fei Shi, Weifang Zhu, Xinjian Chen:
Category feature reconstruction for pathological image segmentation. - Kesi Xu, Mostafa Jahanifar, Simon Graham, Nasir M. Rajpoot:
Accurate segmentation of nuclear instances using a double-stage neural network. - Raghava Vinaykanth Mushunuri, Matthias Choschzick, Ulf-Dietrich Braumann, Juergen Hess:
An ensemble approach for histopathological classification of vulvar cancer.
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last updated on 2024-12-12 21:03 CET by the dblp team
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