Latest AI and machine learning research in pathology for healthcare professionals.
Developing deep learning models to analyze histology images has been computationally challenging, as...
Detecting signet ring cells (SRCs) in pathological images is essential for carcinoma diagnosis. Howe...
This article explores the value of wall F-FDG PET/Cr imaging in the diagnosis of thyroid cancer, stu...
Nowadays, digital pathology plays a major role in the diagnosis and prognosis of tumours. Unfortunat...
The fuzzy C -means (FCM) clustering procedure is an unsupervised form of grouping the homogenous pix...
Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatme...
A better understanding of the tumor immune microenvironment (TIME) could lead to accurate diagnosis,...
The performance characteristics of deep learning fully convolutional neural network (DLFCNN) algorit...
The current gold standard surgical treatment for right colonic malignancy is the laparoscopic right ...
Tissue engineering is a branch of regenerative medicine that harnesses biomaterial and stem cell res...
This study enumerates the quantitative measurement of optical parameters used in several diagnostic ...
BACKGROUND: Current risk stratification for patients with malignant pleural mesothelioma based on di...
PURPOSE: To utilize a neural architecture search (NAS) approach to develop a convolutional neural ne...
Cancers of unknown primary (CUP) are metastatic cancers for which the primary tumor is not found des...
Tissue/region segmentation of pathology images is essential for quantitative analysis in digital pat...
Breast cancer is one among the most frequent reasons of women's death worldwide. Nowadays, healthcar...
Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) is a new b...
In this paper, we propose an automatic cell counting framework for stimulated Raman scattering (SRS)...
Morphological analysis of the bone marrow is an essential step in the diagnosis of hematological dis...
This study focused on the application value of MRI images processed by a Support Vector Machine (SVM...
Image-based biomarker discovery typically requires accurate segmentation of histologic structures (e...