scholarly journals Three-dimensional periodontal investigations using a prototype handheld ultrasound scanner with spatial positioning reading sensor

2021 ◽  
Author(s):  
Radu Chifor ◽  
Mengxun Li ◽  
Kim-Cuong T Nguyen ◽  
Tudor Arsenescu ◽  
Ioana Chifor ◽  
...  
Keyword(s):  
Deep Learning ◽  
Data Processing ◽  
Soft Tissues ◽  
Learning Algorithms ◽  
Three Dimensional ◽  
Movement Analysis ◽  
3D Ultrasound ◽  
Clinical Environment ◽  
Diagnostic Potential ◽  
Spatial Positioning

Aim: To demonstrate the feasibility of the 3D ultrasound periodontal tissue reconstruction of the lateral area of a porcine mandible using standard 2D ultrasound equipment and spatial positioning reading sensors. Material and method: Periodontal 3D reconstructions were performed using a free-hand prototype based on a 2D US scanner and a spatial positioning reading sensor. For automated data processing, deep learning algorithms were implemented and trained using semi-automatically seg-mented images by highly specialized imaging professionals. Results: US probe movement analysis showed that non-parallel 2D frames were acquired during the scanning procedure. Comparing 3 different 3D periodontal reconstructions of the same porcine mandible, the accuracy ranged between 0.179 mm and 0.235 mm. Conclusion: The present study demonstrated the diagnostic potential of 3D reconstruction using a free-hand 2D US scanner with spatial positioning readings. The use of auto-mated data processing with deep learning algorithms makes the process practical in the clinical environment for assessment of periodontal soft tissues.

Developing an Artificial Intelligence Project in your Radiology Department

2020 ◽  
Vol 2 ◽  
pp. 58-61 ◽  
Author(s):  
Syed Junaid ◽  
Asad Saeed ◽  
Zeili Yang ◽  
Thomas Micic ◽  
Rajesh Botchu
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Health Care ◽  
Deep Learning ◽  
Learning Algorithms ◽  
Radiology Department ◽  
Short Article ◽  
Computing Power ◽  
Road Map ◽  
Key Concepts

The advances in deep learning algorithms, exponential computing power, and availability of digital patient data like never before have led to the wave of interest and investment in artificial intelligence in health care. No radiology conference is complete without a substantial dedication to AI. Many radiology departments are keen to get involved but are unsure of where and how to begin. This short article provides a simple road map to aid departments to get involved with the technology, demystify key concepts, and pique an interest in the field. We have broken down the journey into seven steps; problem, team, data, kit, neural network, validation, and governance.

Adult Acquired Flatfoot

2020 ◽  
Vol 62 (1) ◽  
pp. 55-59
Author(s):  
Krzysztof Mataczyński ◽  
Mateusz Pelc ◽  
Halina Romualda Zięba ◽  
Zuzana Hudakova
Keyword(s):  
Soft Tissues ◽  
Three Dimensional ◽  
Clinical Diagnostics ◽  
Clinical Image ◽  
Tibialis Posterior ◽  
Dynamic Force ◽  
Posterior Tibial ◽  
Flat Feet ◽  
Foot Arch ◽  
Motion Range

Acquired adult flatfoot is a three-dimensional deformation, which consists of hindfoot valgus, collapse of the longitudinal arch of the foot and adduction of the forefoot. The aim of the work is to present problems related to etiology, biomechanics, clinical diagnostics and treatment principles of acquired flatfoot. The most common cause in adults is the dysfunction of the tibialis posterior muscle, leading to the lack of blocking of the transverse tarsal joint during heel elevation. Loading the unblocked joints consequently leads to ligament failure. The clinical image is dominated by pain in the foot and tibiotarsal joint. The physical examination of the flat feet consists of: inspection, palpation, motion range assessment and dynamic force assessment. The comparable attention should be paid to the height of the foot arch, the occurrence of “too many toes” sign, evaluate the heel- rise test and correction of the flatfoot, exclude Achilles tendon contracture. The diagnosis also uses imaging tests. In elastic deformations with symptoms of posterior tibial tendonitis, non-steroidal anti-inflammatory drugs, short-term immobilization, orthotics stabilizing the medial arch of the foot are used. In rehabilitation, active exercises of the shin muscles and the feet, especially the eccentric exercises of the posterior tibial muscle, are intentional. The physiotherapy and balneotherapy treatments, in particular hydrotherapy, electrotherapy and laser therapy, are used as a support. In advanced lesions, surgical treatment may be necessary, including plastic surgery of soft tissues, tendons, as well as osteotomy procedures.

3D Culture Modelling: An Emerging Approach for Translational Cancer Research in Sarcomas

2020 ◽  
Vol 27 (29) ◽  
pp. 4778-4788 ◽  
Author(s):  
Victoria Heredia-Soto ◽  
Andrés Redondo ◽  
José Juan Pozo Kreilinger ◽  
Virginia Martínez-Marín ◽  
Alberto Berjón ◽  
...  
Keyword(s):  
High Throughput Screening ◽  
Cancer Biology ◽  
Soft Tissues ◽  
Three Dimensional ◽  
3D Culture ◽  
Resistance Mechanisms ◽  
In Vitro Models ◽  
Tumour Spheroids ◽  
Current Therapies

Sarcomas are tumours of mesenchymal origin, which can arise in bone or soft tissues. They are rare but frequently quite aggressive and with a poor outcome. New approaches are needed to characterise these tumours and their resistance mechanisms to current therapies, responsible for tumour recurrence and treatment failure. This review is focused on the potential of three-dimensional (3D) in vitro models, including multicellular tumour spheroids (MCTS) and organoids, and the latest data about their utility for the study on important properties for tumour development. The use of spheroids as a particularly valuable alternative for compound high throughput screening (HTS) in different areas of cancer biology is also discussed, which enables the identification of new therapeutic opportunities in commonly resistant tumours.

A Study on the Auxiliary Diagnosis of Thyroid Disease Images Based on Multiple Dimensional Deep Learning Algorithms

2020 ◽  
Vol 16 (3) ◽  
pp. 199-205
Author(s):  
Yuejun Liu ◽  
Yifei Xu ◽  
Xiangzheng Meng ◽  
Xuguang Wang ◽  
Tianxu Bai
Keyword(s):  
Deep Learning ◽  
Learning Algorithms ◽  
Region Of Interest ◽  
Classification Performance ◽  
Thyroid Diseases ◽  
Great Success ◽  
Learning Models ◽  
Good Classification Performance ◽  
Spect Images

Background: Medical imaging plays an important role in the diagnosis of thyroid diseases. In the field of machine learning, multiple dimensional deep learning algorithms are widely used in image classification and recognition, and have achieved great success. Objective: The method based on multiple dimensional deep learning is employed for the auxiliary diagnosis of thyroid diseases based on SPECT images. The performances of different deep learning models are evaluated and compared. Methods: Thyroid SPECT images are collected with three types, they are hyperthyroidism, normal and hypothyroidism. In the pre-processing, the region of interest of thyroid is segmented and the amount of data sample is expanded. Four CNN models, including CNN, Inception, VGG16 and RNN, are used to evaluate deep learning methods. Results: Deep learning based methods have good classification performance, the accuracy is 92.9%-96.2%, AUC is 97.8%-99.6%. VGG16 model has the best performance, the accuracy is 96.2% and AUC is 99.6%. Especially, the VGG16 model with a changing learning rate works best. Conclusion: The standard CNN, Inception, VGG16, and RNN four deep learning models are efficient for the classification of thyroid diseases with SPECT images. The accuracy of the assisted diagnostic method based on deep learning is higher than that of other methods reported in the literature.

scholarly journals Deep learning‐based carotid media‐adventitia and lumen‐intima boundary segmentation from three‐dimensional ultrasound images

2019 ◽  
Vol 46 (7) ◽  
pp. 3180-3193 ◽  
Author(s):  
Ran Zhou ◽  
Aaron Fenster ◽  
Yujiao Xia ◽  
J. David Spence ◽  
Mingyue Ding
Keyword(s):  
Deep Learning ◽  
Three Dimensional ◽  
Ultrasound Images
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