Detection of follicular regions in actin-stained whole slide images of the human lymph node by shock filter.
Patrick WurzelJörg AckermannHendrik SchäferSonja ScharfMartin-Leo HansmannIna KochPublished in: Biological chemistry (2020)
Human lymph nodes play a central part of immune defense against infection agents and tumor cells. Lymphoid follicles are compartments of the lymph node which are spherical, mainly filled with B cells. B cells are cellular components of the adaptive immune systems. In the course of a specific immune response, lymphoid follicles pass different morphological differentiation stages. The morphology and the spatial distribution of lymphoid follicles can be sometimes associated to a particular causative agent and development stage of a disease. We report our new approach for the automatic detection of follicular regions in histological whole slide images of tissue sections immuno-stained with actin. The method is divided in two phases: (1) shock filter-based detection of transition points and (2) segmentation of follicular regions. Follicular regions in 10 whole slide images were manually annotated by visual inspection, and sample surveys were conducted by an expert pathologist. The results of our method were validated by comparing with the manual annotation. On average, we could achieve a Zijbendos similarity index of 0.71, with a standard deviation of 0.07.
Keyphrases
- lymph node
- deep learning
- convolutional neural network
- endothelial cells
- immune response
- neoadjuvant chemotherapy
- sentinel lymph node
- loop mediated isothermal amplification
- real time pcr
- optical coherence tomography
- induced pluripotent stem cells
- label free
- machine learning
- pluripotent stem cells
- squamous cell carcinoma
- early stage
- dendritic cells
- inflammatory response
- clinical practice