26 citations · 52 across the 8 of their papers we have counts for
9 papers
Foundation Models -- A Panacea for Artificial Intelligence in Pathology?
Nita Mulliqi, Anders Blilie, Xiaoyi Ji +28
The role of artificial intelligence (AI) in pathology has evolved from aiding diagnostics to uncovering predictive morphological patterns in whole slide images (WSIs). Recently, fo…
Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence Assisted Cancer Diagnosis
Xiaoyi Ji, Richard Salmon, Nita Mulliqi +14
The potential of artificial intelligence (AI) in digital pathology is limited by technical inconsistencies in the production of whole slide images (WSIs), leading to degraded AI pe…
Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer
Liisa Petäinen, Juha P. Väyrynen, Pekka Ruusuvuori +3
Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we propose a method for automated estimation of TSR from histopathological images of…
ACROBAT -- a multi-stain breast cancer histological whole-slide-image data set from routine diagnostics for computational pathology
Philippe Weitz, Masi Valkonen, Leslie Solorzano +15
The analysis of FFPE tissue sections stained with haematoxylin and eosin (H&E) or immunohistochemistry (IHC) is an essential part of the pathologic assessment of surgically resecte…
Deformation equivariant cross-modality image synthesis with paired non-aligned training data
Joel Honkamaa, Umair Khan, Sonja Koivukoski +4
Cross-modality image synthesis is an active research topic with multiple medical clinically relevant applications. Recently, methods allowing training with paired but misaligned da…
Predicting molecular phenotypes from histopathology images: a transcriptome-wide expression-morphology analysis in breast cancer
Yinxi Wang, Kimmo Kartasalo, Masi Valkonen +4
Molecular phenotyping is central in cancer precision medicine, but remains costly and standard methods only provide a tumour average profile. Microscopic morphological patterns obs…
Detection of Perineural Invasion in Prostate Needle Biopsies with Deep Neural Networks
Peter Ström, Kimmo Kartasalo, Pekka Ruusuvuori +6
Background: The detection of perineural invasion (PNI) by carcinoma in prostate biopsies has been shown to be associated with poor prognosis. The assessment and quantification of P…
Virtual reality for 3D histology: multi-scale visualization of organs with interactive feature exploration
Kaisa Liimatainen, Leena Latonen, Masi Valkonen +2
Virtual reality (VR) enables data visualization in an immersive and engaging manner, and it can be used for creating ways to explore scientific data. Here, we use VR for visualizat…
Pathologist-Level Grading of Prostate Biopsies with Artificial Intelligence
Peter Ström, Kimmo Kartasalo, Henrik Olsson +29
Background: An increasing volume of prostate biopsies and a world-wide shortage of uro-pathologists puts a strain on pathology departments. Additionally, the high intra- and inter-…