# Feasibility of Bone Mineral Density and Bone Microarchitecture Assessment Using Deep Learning With a Convolutional Neural Network

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/feasibility-of-bone-mineral-density-and-bone-microarchitecture-assessment-using/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Kazuki Yoshida,Yuki Tanabe,Hikaru Nishiyama,Takuya Matsuda,Hidetaka Toritani,Takuya Kitamura,Shin‐ichiro Sakai,Kunihiko Watamori,Masaki Takao,Eizen Kimura,Teruhito Kido |
| Citations | 11 |
| DOI | 10.1097/rct.0000000000001437 |
| Fields | Engineering,Medicine |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://doi.org/10.1097/rct.0000000000001437 |
| OpenAlex ID | https://openalex.org/W4376619916 |
| PMID | 37185012 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Kunihiko Watamori](https://scholariq.org/researchers/kunihiko-watamori/)

## Paper primary topic

- [Bone health and osteoporosis research](https://scholariq.org/topics/bone-health-and-osteoporosis-research/)

## Paper topics

- [Bone health and osteoporosis research](https://scholariq.org/topics/bone-health-and-osteoporosis-research/)
- [Medical Imaging and Analysis](https://scholariq.org/topics/medical-imaging-and-analysis/)
- [Bone and Joint Diseases](https://scholariq.org/topics/bone-and-joint-diseases/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.