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Bone Marrow

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Optimized deep learning networks for accurate identification of cancer cells in bone marrow.

Neural networks : the official journal of the International Neural Network Society
Radiologists utilize pictures from X-rays, magnetic resonance imaging, or computed tomography scans to diagnose bone cancer. Manual methods are labor-intensive and may need specialized knowledge. As a result, creating an automated process for disting...

Automatic segmentation and visualization of cortical and marrow bone in mandibular condyle on CBCT: a preliminary exploration of clinical application.

Oral radiology
OBJECTIVES: To develop a deep learning-based automatic segmentation method for cortex and marrow in mandibular condyle on cone-beam computed tomography (CBCT) images and explore its clinical application.

Development and validation of a deep learning model for morphological assessment of myeloproliferative neoplasms using clinical data and digital pathology.

British journal of haematology
The subjectivity of morphological assessment and the overlapping pathological features of different subtypes of myeloproliferative neoplasms (MPNs) make accurate diagnosis challenging. To improve the pathological assessment of MPNs, we developed a di...

Machine learning based on multiplatform tests assists in subtype classification of mature B-cell neoplasms.

British journal of haematology
Mature B-cell neoplasms (MBNs) are clonal proliferative diseases encompassing over 40 subtypes. The WHO classification (morphology, immunology, cytogenetics and molecular biology) provides comprehensive diagnostic understandings. However, MBN subtypi...

Using artificial intelligence-based software for an unbiased discrimination of immune cell subtypes in the fracture hematoma and bone marrow of non-osteoporotic and osteoporotic mice.

PloS one
It is well established that the early inflammatory response following fracture is essential for initiating subsequent bone regeneration. An imbalance in inflammation, whether within the innate or adaptive immune response, can result in impaired fract...

Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank.

Nature communications
Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. Here, w...

A deep-learning algorithm (AIFORIA) for classification of hematopoietic cells in bone marrow aspirate smears based on nine cell classes-a feasible approach for routine screening?

Journal of hematopathology
Bone marrow cytology plays a key role for the diagnosis and classification of hematological disease and is often the first step in the acute setting of unclear cytopenia. AI applications represent a powerful tool in digital image analysis and can imp...

Improved MRI detection of inflammation-induced changes in bone marrow microstructure in mice: a machine learning-enhanced T2 distribution analysis.

European radiology experimental
BACKGROUND: We investigated inflammation-induced changes in femoral hematopoietic bone marrow using advanced magnetic resonance imaging (MRI) techniques, including T2-weighted imaging, scalar T2 mapping, and machine learning-enhanced T2 distribution ...

Multimodal representations of transfer learning with snake optimization algorithm on bone marrow cell classification using biomedical histopathological images.

Scientific reports
Bone marrow (BM) plays a crucial role in the hematopoietic process, producing all of the body's blood cells and maintaining the overall immune and health system. Red and yellow BM are the two various kinds of BM. A comprehensive identification of the...