AIMC Topic: Lymphocytes

Clear Filters Showing 11 to 20 of 56 articles

Immunohistochemistry annotations enhance AI identification of lymphocytes and neutrophils in digitized H&E slides from inflammatory bowel disease.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Histologic assessment of the immune infiltrate in H&E slides is vital in diagnosing and managing inflammatory bowel diseases, but these assessments are subjective and time-consuming even for those with expertise. The develop...

Automatic classification of acute lymphoblastic leukemia cells and lymphocyte subtypes based on a novel convolutional neural network.

Microscopy research and technique
Acute lymphoblastic leukemia (ALL) is a life-threatening disease that commonly affects children and is classified into three subtypes: L1, L2, and L3. Traditionally, ALL is diagnosed through morphological analysis, involving the examination of blood ...

Comparison of Sysmex XN-V body fluid mode and deep-learning-based quantification with manual techniques for total nucleated cell count and differential count for equine bronchoalveolar lavage samples.

BMC veterinary research
BACKGROUND: Bronchoalveolar lavage (BAL) is a diagnostic method for the assessment of the lower respiratory airway health status in horses. Differential cell count and sometimes also total nucleated cell count (TNCC) are routinely measured by time-co...

Association between neutrophil-to-lymphocyte ratio and diabetic kidney disease in type 2 diabetes mellitus patients: a cross-sectional study.

Frontiers in endocrinology
AIMS: This investigation examined the possibility of a relationship between neutrophil-to-lymphocyte ratio (NLR) and diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients.

Artificial intelligence and the blood film: Performance of the MC-80 digital morphology analyzer in samples with neoplastic and reactive cell types.

International journal of laboratory hematology
INTRODUCTION: Implementing artificial intelligence-based instruments in hematology laboratories requires evidence of efficiency in classifying pathological cells. In two-Universities, we assessed the performance of the Mindray® MC-80 for hematology p...

Deep learning as a new tool in the diagnosis of mycosis fungoides.

Archives of dermatological research
Mycosis Fungoides (MF) makes up the most of the cutaneous lymphomas. As a malignant disease, the greatest diagnostical challenge is to timely differentiate MF from inflammatory diseases. Contemporary computational methods successfully identify cell n...

Automatic generation of artificial images of leukocytes and leukemic cells using generative adversarial networks (syntheticcellgan).

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Visual analysis of cell morphology has an important role in the diagnosis of hematological diseases. Morphological cell recognition is a challenge that requires experience and in-depth review by clinical pathologists. Withi...

White blood cell detection, classification and analysis using phase imaging with computational specificity (PICS).

Scientific reports
Treatment of blood smears with Wright's stain is one of the most helpful tools in detecting white blood cell abnormalities. However, to diagnose leukocyte disorders, a clinical pathologist must perform a tedious, manual process of locating and identi...

Deep Learning Model for the Automatic Classification of White Blood Cells.

Computational intelligence and neuroscience
Blood cell count is highly useful in identifying the occurrence of a particular disease or ailment. To successfully measure the blood cell count, sophisticated equipment that makes use of invasive methods to acquire the blood cell slides or images is...

A Machine Learning Tool Using Digital Microscopy (Morphogo) for the Identification of Abnormal Lymphocytes in the Bone Marrow.

Acta cytologica
Morphological analysis of the bone marrow is an essential step in the diagnosis of hematological disease. The conventional analysis of bone marrow smears is performed under a manual microscope, which is labor-intensive and subject to interobserver va...