Leslie Solorzano

Towards automatic protein co-expression quantification in immunohistochemical TMA slides

Solorzano, Leslie; Pereira, Carla; Martins, Diana; Almeida, Raquel et al.

Part of IEEE journal of biomedical and health informatics, p. 393-402, 2021

• DOI for Towards automatic protein co-expression quantification in immunohistochemical TMA slides
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Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study

Strom, Peter; Kartasalo, Kimmo; Olsson, Henrik; Solorzano, Leslie et al.

Part of The Lancet Oncology, p. 222-232, 2020

• DOI for Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study

TissUUmaps: interactive visualization of large-scale spatial gene expression and tissue morphology data

Solorzano, Leslie; Partel, Gabriele; Wählby, Carolina

Part of Bioinformatics, p. 4363-4365, 2020

• DOI for TissUUmaps: interactive visualization of large-scale spatial gene expression and tissue morphology data
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Deep Learning in Image Cytometry: A Review

Gupta, Anindya; Harrison, Philip J.; Wieslander, Håkan; Pielawski, Nicolas et al.

Part of Cytometry Part A, p. 366-380, 2019

• DOI for Deep Learning in Image Cytometry: A Review
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Whole Slide Image Registration for the Study of Tumor Heterogeneity

Solorzano, Leslie; Almeida, Gabriela; Mesquita, Bárbara; Martins, Diana et al.

Part of MICCAI 2018 - International Workshop on Ophthalmic Medical Image Analysis, p. 95-102, 2018

• DOI for Whole Slide Image Registration for the Study of Tumor Heterogeneity

TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data

Pielawski, Nicolas; Andersson, Axel; Avenel, Christophe; Beháňová, Andrea et al.

Part of Heliyon, 2023

• DOI for TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data
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Improved breast cancer histological grading using deep learning

Wang, Y.; Acs, B.; Robertson, S.; Liu, B. et al.

Part of Annals of Oncology, p. 89-98, 2022

• DOI for Improved breast cancer histological grading using deep learning
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Towards automatic protein co-expression quantification in immunohistochemical TMA slides

Solorzano, Leslie; Pereira, Carla; Martins, Diana; Almeida, Raquel et al.

Part of IEEE journal of biomedical and health informatics, p. 393-402, 2021

• DOI for Towards automatic protein co-expression quantification in immunohistochemical TMA slides
• Download full text 1 (pdf) of Towards automatic protein co-expression quantification in immunohistochemical TMA slides
• Download full text 2 (pdf) of Towards automatic protein co-expression quantification in immunohistochemical TMA slides

Machine learning for cell classification and neighborhood analysis in glioma tissue

Solorzano, Leslie; Wik, Lina; Bontell, Thomas Olsson; Wang, Yuyu et al.

Part of Cytometry Part A, p. 1176-1186, 2021

• DOI for Machine learning for cell classification and neighborhood analysis in glioma tissue
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Image Processing, Machine Learning and Visualization for Tissue Analysis

Solorzano, Leslie

2021

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TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data

Pielawski, Nicolas; Andersson, Axel; Avenel, Christophe; Beháňová, Andrea et al.

Part of Heliyon, 2023

• DOI for TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data
• Download full text (pdf) of TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data

Improved breast cancer histological grading using deep learning

Wang, Y.; Acs, B.; Robertson, S.; Liu, B. et al.

Part of Annals of Oncology, p. 89-98, 2022

• DOI for Improved breast cancer histological grading using deep learning
• Download full text (pdf) of Improved breast cancer histological grading using deep learning

Towards automatic protein co-expression quantification in immunohistochemical TMA slides

Solorzano, Leslie; Pereira, Carla; Martins, Diana; Almeida, Raquel et al.

Part of IEEE journal of biomedical and health informatics, p. 393-402, 2021

• DOI for Towards automatic protein co-expression quantification in immunohistochemical TMA slides
• Download full text 1 (pdf) of Towards automatic protein co-expression quantification in immunohistochemical TMA slides
• Download full text 2 (pdf) of Towards automatic protein co-expression quantification in immunohistochemical TMA slides

Machine learning for cell classification and neighborhood analysis in glioma tissue

Solorzano, Leslie; Wik, Lina; Bontell, Thomas Olsson; Wang, Yuyu et al.

Part of Cytometry Part A, p. 1176-1186, 2021

• DOI for Machine learning for cell classification and neighborhood analysis in glioma tissue
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Comparison of East‐Asia and West‐Europe cohorts explains disparities in survival outcomes and highlights predictive biomarkers of early gastric cancer aggressiveness

Pereira, Carla; Park, Ji‐Hyeon; Campelos, Sofia; Gullo, Irene et al.

Part of International Journal of Cancer, p. 868-880, 2021

• DOI for Comparison of East‐Asia and West‐Europe cohorts explains disparities in survival outcomes and highlights predictive biomarkers of early gastric cancer aggressiveness

Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study

Strom, Peter; Kartasalo, Kimmo; Olsson, Henrik; Solorzano, Leslie et al.

Part of The Lancet Oncology, p. 222-232, 2020

• DOI for Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study

TissUUmaps: interactive visualization of large-scale spatial gene expression and tissue morphology data

Solorzano, Leslie; Partel, Gabriele; Wählby, Carolina

Part of Bioinformatics, p. 4363-4365, 2020

• DOI for TissUUmaps: interactive visualization of large-scale spatial gene expression and tissue morphology data
• Download full text (pdf) of TissUUmaps: interactive visualization of large-scale spatial gene expression and tissue morphology data

Automated identification of the mouse brain’s spatial compartments from in situ sequencing data

Partel, Gabriele; Hilscher, Markus M.; Milli, Giorgia; Solorzano, Leslie et al.

Part of BMC Biology, 2020

• DOI for Automated identification of the mouse brain’s spatial compartments from in situ sequencing data
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Voxel-wise assessment of lung aeration changes on CT images using image registration: a: application to acute respiratory distress syndrome (ARDS)

Orkisz, Maciej; Morales, Alfredo; Richard, Jean-Christophe; Guerin, Claude et al.

Part of International Journal of Computer Assisted Radiology and Surgery, p. 1-9, 2019

• DOI for Voxel-wise assessment of lung aeration changes on CT images using image registration: a: application to acute respiratory distress syndrome (ARDS)

Deep Learning in Image Cytometry: A Review

Gupta, Anindya; Harrison, Philip J.; Wieslander, Håkan; Pielawski, Nicolas et al.

Part of Cytometry Part A, p. 366-380, 2019

• DOI for Deep Learning in Image Cytometry: A Review
• Download full text (pdf) of Deep Learning in Image Cytometry: A Review

Image Processing, Machine Learning and Visualization for Tissue Analysis

Solorzano, Leslie

2021

• Download full text (pdf) of Image Processing, Machine Learning and Visualization for Tissue Analysis

Transcriptome-Supervised Classification of Tissue Morphology Using Deep Learning

Andersson, Axel; Partel, Gabriele; Solorzano, Leslie; Wählby, Carolina

Part of IEEE 17th International Symposium on Biomedical Imaging (ISBI), p. 1630-1633, 2020

• DOI for Transcriptome-Supervised Classification of Tissue Morphology Using Deep Learning

Whole Slide Image Registration for the Study of Tumor Heterogeneity

Solorzano, Leslie; Almeida, Gabriela; Mesquita, Bárbara; Martins, Diana et al.

Part of MICCAI 2018 - International Workshop on Ophthalmic Medical Image Analysis, p. 95-102, 2018

• DOI for Whole Slide Image Registration for the Study of Tumor Heterogeneity

Decoding gene expression in 2D and 3D

Bombrun, Maxime; Ranefall, Petter; Lindblad, Joakim; Allalou, Amin et al.

Part of Image Analysis, p. 257-268, 2017

• DOI for Decoding gene expression in 2D and 3D
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Pathologist-Level Grading of Prostate Biospies with Artificial intelligence

Ström, Peter; Kartasalo, Kimmo; Olsson, Henrik; Solorzano, Leslie et al.

Identification of spatial compartments in tissue from in situ sequencing data

Partel, Gabriele; Hilscher, Markus M.; Giorgia, Milli; Solorzano, Leslie et al.

• DOI for Identification of spatial compartments in tissue from in situ sequencing data

TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data

Pielawski, Nicolas; Andersson, Axel; Avenel, Christophe; Behanova, Andrea et al.

• Download full text (pdf) of TissUUmaps 3: Improvements in interactive visualization, exploration, and quality assessment of large-scale spatial omics data