Apr 29, 2021 · We have used a deep convolutional neural network (DCNN) as a semantic segmentation model to segment seven different tumour regions.

Abstract. We describe a new technique to automatically segment and track the cell images of a breast cancer cell line in order to study cell.

Jun 13, 2022 · The StarDist segmentations closely follow the cell outline in most cases, enabling precise quantification of signal intensities. These ...

Jul 16, 2024 · This is the first feasibility study that evaluated utility of automated segmentation for thyroid cancer detection at the cellular level using ...

Sep 21, 2023 · One of the mainstream methods for automated cervical cancer cytology screening is cell segmentation followed by single cell classification.

We adopt methods from ab initio cell simulation to rapidly infer morphologically plausible cell boundaries that preserve cell type heterogeneity.

Deep learning methods, particularly convolutional neural networks (CNNs), have shown great success in improving cell segmentation accuracy.

The proposed segmentation method is tested on a large dataset containing several breast cancer cell images with different levels of malignancy. The experimental ...

Cell segmentation is the process of identifying and separating individual cells within an image, which is crucial for disease diagnosis and classification.

Jun 8, 2024 · In this research, H&E stained cancer cell images are labeled manually, and segmentation is performed by transfer learning using a conventional method to ...