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Bone Marrow

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Unsupervised flow cytometry analysis in hematological malignancies: A new paradigm.

International journal of laboratory hematology
Ever since hematopoietic cells became "events" enumerated and characterized in suspension by cell counters or flow cytometers, researchers and engineers have strived to refine the acquisition and display of the electronic signals generated. A large a...

Screening For Bone Marrow Cellularity Changes in Cynomolgus Macaques in Toxicology Safety Studies Using Artificial Intelligence Models.

Toxicologic pathology
Many compounds affect the cellularity of hematolymphoid organs including bone marrow. Toxicologic pathologists are tasked with their evaluation as part of safety studies. An artificial intelligence (AI) tool could provide diagnostic support for the p...

Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis.

Nature communications
Single-cell RNA sequencing (scRNA-seq) can characterize cell types and states through unsupervised clustering, but the ever increasing number of cells and batch effect impose computational challenges. We present DESC, an unsupervised deep embedding a...

Efficient Classification of White Blood Cell Leukemia with Improved Swarm Optimization of Deep Features.

Scientific reports
White Blood Cell (WBC) Leukaemia is caused by excessive production of leukocytes in the bone marrow, and image-based detection of malignant WBCs is important for its detection. Convolutional Neural Networks (CNNs) present the current state-of-the-art...

Automatic Vertebral Body Segmentation Based on Deep Learning of Dixon Images for Bone Marrow Fat Fraction Quantification.

Frontiers in endocrinology
Bone marrow fat (BMF) fraction quantification in vertebral bodies is used as a novel imaging biomarker to assess and characterize chronic lower back pain. However, manual segmentation of vertebral bodies is time consuming and laborious. (1) Develop...

Morphogo: An Automatic Bone Marrow Cell Classification System on Digital Images Analyzed by Artificial Intelligence.

Acta cytologica
INTRODUCTION: The nucleated-cell differential count on the bone marrow aspirate smears is required for the clinical diagnosis of hematological malignancy. Manual bone marrow differential count is time consuming and lacks consistency. In this study, a...

[A Case of Disseminated Carcinomatosis of the Bone Marrow Developing 15 Months after Gastrectomy].

Gan to kagaku ryoho. Cancer & chemotherapy
The patient was a 60-year-old man who underwent distal gastrectomy for gastric cancer. The pathological diagnosis was Stage ⅡB. He received adjuvant chemotherapy(capecitabine plus oxaliplatin: CapeOX)for 6months and the postoperative course was uneve...

Automated Flow Cytometric MRD Assessment in Childhood Acute B- Lymphoblastic Leukemia Using Supervised Machine Learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Minimal residual disease (MRD) as measured by multiparameter flow cytometry (FCM) is an independent and strong prognostic factor in B-cell acute lymphoblastic leukemia (B-ALL). However, reliable flow cytometric detection of MRD strongly depends on op...

Simultaneous Cell Detection and Classification in Bone Marrow Histology Images.

IEEE journal of biomedical and health informatics
Recently, deep learning frameworks have been shown to be successful and efficient in processing digital histology images for various detection and classification tasks. Among these tasks, cell detection and classification are key steps in many comput...