Making densenet interpretable a case study in clinical radiology

Ngan, Kwun Ho; Garcez, Artur d’Avila; Knapp, Karen; Appelboam, Andy; Reyes-Aldasoro, Constantino Carlos

doi:10.1101/19013730

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…Furthermore, the prospect of replacing the semi-automatic nature of the methodology with a fully automatic should be explored. This includes the February 18, 2020 6/14 possible option to incorporate the use of convolution neural networks for automatic detection of the radius [36,37] and fracture diagnosis [38].…”

Section: Discussionmentioning

confidence: 99%

Geometric Semi-automatic Analysis of Colles’ Fractures

Reyes-Aldasoro

Ngan

Ananda

et al. 2020

Preprint

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Fractures of the wrist are common in Emergency Departments, where some patients are treated with a procedure called Manipulation under Anaesthesia. In some cases this procedure is unsuccessful and patients need to visit the hospital again where they undergo surgery to treat the fracture. This work describes a geometric semi-automatic image analysis algorithm to analyse and compare the x-rays of healthy controls and patients with dorsally displaced wrist fractures (Colles' fractures) who were treated with Manipulation under Anaesthesia. A series of 161 posterior-anterior radiographs from healthy controls and patients with Colles' fractures were acquired and analysed. The patients' group was further subdivided according to the outcome of the procedure (successful/unsuccessful) and pre- or post-intervention creating five groups in total (healthy, pre-successful, pre-unsuccessful, post-successful, post-unsuccessful). The semi-automatic analysis consisted of manual location of three landmarks (finger, lunate and radial styloid) and automatic processing to generate 32 geometric and texture measurements, which may be related to conditions such as osteoporosis and swelling of the wrist. Statistical differences were found between patients and controls and pre- and post-intervention, but not between the procedures. The most distinct measurements were those of texture. Although the study includes a relatively low number of cases and measurements, the statistical differences are encouraging.

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Section: Discussionmentioning

confidence: 99%

Geometric Semi-automatic Analysis of Colles’ Fractures

Reyes-Aldasoro

Ngan

Ananda

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Also, the prospect of replacing the semi-automatic nature of the methodology with a fully automatic should be explored. This includes the possible option to incorporate the use of convolution neural networks for automatic detection of the radius [ 51 , 52 ] and fracture diagnosis [ 53 ].…”

Section: Discussionmentioning

confidence: 99%

Geometric semi-automatic analysis of radiographs of Colles’ fractures

et al. 2020

Self Cite

View full text Add to dashboard Cite

Fractures of the wrist are common in Emergency Departments, where some patients are treated with a procedure called Manipulation under Anaesthesia. In some cases, this procedure is unsuccessful and patients need to revisit the hospital where they undergo surgery to treat the fracture. This work describes a geometric semi-automatic image analysis algorithm to analyse and compare the x-rays of healthy controls and patients with dorsally displaced wrist fractures (Colles’ fractures) who were treated with Manipulation under Anaesthesia. A series of 161 posterior-anterior radiographs from healthy controls and patients with Colles’ fractures were acquired and analysed. The patients’ group was further subdivided according to the outcome of the procedure (successful/unsuccessful) and pre- or post-intervention creating five groups in total (healthy, pre-successful, pre-unsuccessful, post-successful, post-unsuccessful). The semi-automatic analysis consisted of manual location of three landmarks (finger, lunate and radial styloid) and automatic processing to generate 32 geometric and texture measurements, which may be related to conditions such as osteoporosis and swelling of the wrist. Statistical differences were found between patients and controls, as well as between pre- and post-intervention, but not between the procedures. The most distinct measurements were those of texture. Although the study includes a relatively low number of cases and measurements, the statistical differences are encouraging.

show abstract