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Description

Osteomyelitis may be classified as Bacterial (Actinomycotic), Fungal (Mucormycotic), or combined based on the etiological agent. During histopathological examination, there is a high chance that bacterial colonies or fungal hyphae may be missed by the human eye, especially when there is a paucity of organisms. This may lead to a faulty diagnosis of the type of osteomyelitis which along with an improper treatment plan would cause further progression of the disease and various other complications. Therefore, the diagnosis of the exact etiological variant of osteomyelitis is of prime importance to design an appropriate treatment plan. In the present study, bone parameters based on the osseous changes, were used to diagnose Osteomyelitis by employing Machine Learning through Convolutional Neural Networks (CNN). No studies in literature have utilized a CNN based analysis to differentiate between Bacterial and Fungal Osteomyelitis based on the osseous changes which would help in designing an appropriate treatment plan.

Disciplines

Bacteria | Bacterial Infections and Mycoses | Fungi | Medical Sciences | Medicine and Health Sciences | Oral Biology and Oral Pathology

Document Type

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Convolutional Neural Network Based Analysis - An Aid to Diagnose Bacterial and Fungal Osteomyelitis

Osteomyelitis may be classified as Bacterial (Actinomycotic), Fungal (Mucormycotic), or combined based on the etiological agent. During histopathological examination, there is a high chance that bacterial colonies or fungal hyphae may be missed by the human eye, especially when there is a paucity of organisms. This may lead to a faulty diagnosis of the type of osteomyelitis which along with an improper treatment plan would cause further progression of the disease and various other complications. Therefore, the diagnosis of the exact etiological variant of osteomyelitis is of prime importance to design an appropriate treatment plan. In the present study, bone parameters based on the osseous changes, were used to diagnose Osteomyelitis by employing Machine Learning through Convolutional Neural Networks (CNN). No studies in literature have utilized a CNN based analysis to differentiate between Bacterial and Fungal Osteomyelitis based on the osseous changes which would help in designing an appropriate treatment plan.