A comparison of deep learning and hand crafted features in medical image modality classification
S Khan, SP Yong - 2016 3rd International Conference on …, 2016 - ieeexplore.ieee.org
Modality corresponding to medical images is a vital filter in medical image retrieval systems,
as radiologists or physicians are interested in only one of radiology images eg CT scan …
as radiologists or physicians are interested in only one of radiology images eg CT scan …
Applying 3D texture algorithms on MRI to evaluate quality traits of loin
This study firstly proposed the use of 3D MRI images to analyze loins in a non-destructive
way. For that, interpolation and reconstruction techniques are applied on 2D MRI images of …
way. For that, interpolation and reconstruction techniques are applied on 2D MRI images of …
RenseNet: A Deep Learning Network Incorporating Residual and Dense Blocks with Edge Conservative Module to Improve Small-Lesion Classification and Model …
Simple Summary Small-target classification in an image is still challenging in spite of
emerging deep learning-based techniques. This study focused on the development of deep …
emerging deep learning-based techniques. This study focused on the development of deep …
Detecting the modality of a medical image using visual and textual features
Knowing the modality of a medical image is crucial in understanding the characteristics of
the image. Therefore, it is important to classify medical images as per their modality. The …
the image. Therefore, it is important to classify medical images as per their modality. The …
Ensemble classification with modified sift descriptor for medical image modality
The increasing number of medical images of various imaging modalities is challenging the
accuracy and efficiency of radiologists. In order to retrieve the images from medical …
accuracy and efficiency of radiologists. In order to retrieve the images from medical …
[PDF][PDF] An Image Mining Approach to Classify Dental Images into Normal and Caries-Infected using a Reduced Textural Feature Set.
Image mining is an emerging research field in the digital era. Medical image mining is
critical and challenging as medical images contain vital information for characterizing health …
critical and challenging as medical images contain vital information for characterizing health …
A comparative evaluation of features for medical image modality classification
Medical images are increasing at an alarming rate. This increasing number of images affects
the interpreting capacity of radiologists. In order to reduce the burden of radiologists …
the interpreting capacity of radiologists. In order to reduce the burden of radiologists …
[PDF][PDF] Text-based Medical Image Retrieval using Query Modification Methods
This paper presents a strategy for text-based retrieval of medical images by applying query
modification. The goal of the paper is to investigate whether query modification techniques …
modification. The goal of the paper is to investigate whether query modification techniques …
Deep Learning for data analysis on specific contexts (Automotive, Medical Imaging)
F Trenta - 2022 - tesidottorato.depositolegale.it
In light of the tremendous success gained by Deep Learning algorithms, the role of these
techniques is becoming increasingly important in the challenging automotive and healthcare …
techniques is becoming increasingly important in the challenging automotive and healthcare …
Applying 3D texture algorithms on MRI to evaluate quality traits of loin
MM Ávila Vegas, D Caballero, ML Durán Martín-Merás… - 2018 - dehesa.unex.es
This study firstly proposed the use of 3D MRI images to analyze loins in a non-destructive
way. For that, interpolation and reconstruction techniques are applied on 2D MRI images of …
way. For that, interpolation and reconstruction techniques are applied on 2D MRI images of …