Training based cell detection from bright-field microscope images. - Tuomas Tikkanen; Pekka Ruusuvuori; Leena Latonen; Heikki Huttunen (ISPA, 2015)

Benchmarking of algorithms for 3D tissue reconstruction. - Kimmo Kartasalo; Leena Latonen; Tapio Visakorpi; Matti Nykter; Pekka Ruusuvuori (ICIP, 2016)

Supervised method for cell counting from bright field focus stacks. - Kaisa Liimatainen; Pekka Ruusuvuori; Leena Latonen; Heikki Huttunen (ISBI, 2016)

Dual Structured Convolutional Neural Network with Feature Augmentation for Quantitative Characterization of Tissue Histology. - Mira Valkonen; Kimmo Kartasalo; Kaisa Liimatainen; Matti Nykter; Leena Latonen; Pekka Ruusuvuori (ICCV Workshops, 2017)

Comparative analysis of tissue reconstruction algorithms for 3D histology. - Kimmo Kartasalo; Leena Latonen; Jorma Vihinen; Tapio Visakorpi; Matti Nykter; Pekka Ruusuvuori (Bioinform., 2018)

3D-Printed Whole Prostate Models with Tumor Hotspots Using Dual-Extruder Printer. - Kaisa Liimatainen; Leena Latonen; Kimmo Kartasalo; Pekka Ruusuvuori (EMBC, 2019)

Iterative unsupervised domain adaptation for generalized cell detection from brightfield z-stacks. - Kaisa Liimatainen; Lauri Kananen; Leena Latonen; Pekka Ruusuvuori (BMC Bioinform., 2019)

Virtual reality for 3D histology: multi-scale visualization of organs with interactive feature exploration. - Kaisa Liimatainen; Leena Latonen; Masi Valkonen; Kimmo Kartasalo; Pekka Ruusuvuori (CoRR, 2020)

ANHIR: Automatic Non-Rigid Histological Image Registration Challenge. - Jirí Borovec; Jan Kybic; Ignacio Arganda-Carreras; Dmitry V. Sorokin; Gloria Bueno; Alexander V. Khvostikov; Spyridon Bakas; Eric I-Chao Chang; Stefan Heldmann; Kimmo Kartasalo; Leena Latonen; Johannes Lotz 002; et al. (IEEE Trans. Medical Imaging, 2020)

A systematic comparison of data- and knowledge-driven approaches to disease subtype discovery. - Teemu J. Rintala; Antonio Federico; Leena Latonen; Dario Greco; Vittorio Fortino (Briefings Bioinform., 2021)

Deformation equivariant cross-modality image synthesis with paired non-aligned training data. - Joel Honkamaa; Umair Khan; Sonja Koivukoski; Leena Latonen; Pekka Ruusuvuori; Pekka Marttinen (CoRR, 2022)

ACROBAT - a multi-stain breast cancer histological whole-slide-image data set from routine diagnostics for computational pathology. - Philippe Weitz; Masi Valkonen; Leslie Solorzano; Circe Carr; Kimmo Kartasalo; Constance Boissin; Sonja Koivukoski; Aino Kuusela; Dusan Rasic; Yanbo Feng; Sandra Kristiane Sinius Pouplier; Abhinav Sharma; et al. (CoRR, 2022)

The effect of neural network architecture on virtual H&E staining: Systematic assessment of histological feasibility. - Umair Khan; Sonja Koivukoski; Mira Valkonen; Leena Latonen; Pekka Ruusuvuori (Patterns, 2023)

Deformation equivariant cross-modality image synthesis with paired non-aligned training data. - Joel Honkamaa; Umair Khan; Sonja Koivukoski; Mira Valkonen; Leena Latonen; Pekka Ruusuvuori; Pekka Marttinen (Medical Image Anal., 2023)

The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue. - Philippe Weitz; Masi Valkonen; Leslie Solorzano; Circe Carr; Kimmo Kartasalo; Constance Boissin; Sonja Koivukoski; Aino Kuusela; Dusan Rasic; Yanbo Feng; Sandra Kristiane Sinius Pouplier; Abhinav Sharma; et al. (Medical Image Anal., 2024)

Staining normalization in histopathology: Method benchmarking using multicenter dataset. - Umair Khan; Jouni Härkönen; Marjukka Friman; Leena Latonen; Teijo Kuopio; Pekka Ruusuvuori (CoRR, 2025)