Bone marrow histology was the indispensable tool for the differential diagnosis of classic myeloproliferative neoplasms (MPNs) and subtypes. However, the subjectivity of morphological assessment and markedly overlapping pathological features of different subtypes made accurate diagnosis challenging and controversial.
In this study, we developed Clinical, deep learning (DL) and Fusion diagnosis models based on clinical parameters, whole slide images (WSI) based deep learning algorithm using hematoxylin-eosin (HE) staining bone marrow specimen and combination of both for the diagnosis and differentiation of MPNs.
- VGG16
- RestNet50
- DensenNet121
- Inception v3
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Identifying CLL cells from normal cells
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Identifying CLL cells from normal cells mixed of virus infected cells
