A new framwork based on the trilateral filter for despeckling ultrasoud images

Moussa, Olfa; Khlifa, Nawrès

doi:10.1109/codit.2016.7593650

Cited by 3 publications

(1 citation statement)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, the image preprocessing is the basic requirement to provide a better “input” for the next CAD system steps. An important number of research works have been developed to achieve this objective. These steps are ordered as follows: the extraction of the ROI and the extraction of relevant features from the ROIs for the classification.…”

Section: Introductionmentioning

confidence: 99%

Thyroid nodules classification and diagnosis in ultrasound images using fine‐tuning deep convolutional neural network

Moussa

Khachnaoui

Guetari

et al. 2019

Int J Imaging Syst Tech

View full text Add to dashboard Cite

Ultrasonography AKA diagnostic sonography is a noninvasive imaging technique that allows the analysis of an organic structure, thanks to the ultrasonic waves. It is a valuable diagnosis method and is also seen as the evidence‐based diagnostic method for thyroid nodules. The diagnosis, however, is visually made by the practitioner. The automatic discrimination of benign and malignant nodules would be very useful to report Thyroid Imaging Reporting. In this paper, we propose a fine‐tuning approach based on deep learning using a Convolutional Neural Network model named resNet‐50. This approach allows improving the effectiveness of the classification of thyroid nodules in ultrasound images. Experiments have been conducted on 814 ultrasound images and the results show that our proposed approach dramatically improves the accuracy of the classification of thyroid nodules and outperforms The VGG‐19 model.

show abstract

Section: Introductionmentioning

confidence: 99%