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, organised group exercise and cooking activities) might help to enhance healthy lifestyle approaches within AOD treatment settings.

The capability of deep learning radiomics (DLR) to extract high-level medical imaging features has promoted the use of computer-aided diagnosis of breast mass detected on ultrasound. Recently, generative adversarial network (GAN) has aided in tackling a general issue in DLR, i.e., obtaining a sufficient number of medical images. However, GAN methods require a pair of input and labeled images, which require an exhaustive human annotation process that is very time-consuming. The aim of this paper is to develop a radiomics model based on a semi-supervised GAN method to perform data augmentation in breast ultrasound images.

A total of 1447 ultrasound images, including 767 benign masses and 680 malignant masses were acquired from a tertiary hospital. A semi-supervised GAN model was developed to augment the breast ultrasound images. learn more The synthesized images were subsequently used to classify breast masses using a convolutional neural network (CNN). The model was validated using a 5-fold cross-validation method.

The proposed GAN architecture generated high-quality breast ultrasound images, verified by two experienced radiologists. The improved performance of semi-supervised learning increased the quality of the synthetic data produced in comparison to the baseline method. We achieved more accurate breast mass classification results (accuracy 90.41%, sensitivity 87.94%, specificity 85.86%) with our synthetic data augmentation compared to other state-of-the-art methods.

The proposed radiomics model has demonstrated a promising potential to synthesize and classify breast masses on ultrasound in a semi-supervised manner.

The proposed radiomics model has demonstrated a promising potential to synthesize and classify breast masses on ultrasound in a semi-supervised manner.

During capsulotomy, the force applied to the anterior capsule is a crucial parameter controlling capsule tears, that affects the clinical performance. This study aims to investigate the tear force in capsulotomy and analyze the effects of different tearing conditions on the tear force.

A three-dimensional model of the human lens was constructed based on published clinical data using the finite element (FE) method. The lens model consisted of four layers the anterior and posterior lens capsule, the cortex, and the nucleus. Distortion energy failure criterion combined with the bilinear interface law was used to express the crack propagation process at the edge of the anterior lens capsule. At the clamping position, a local coordinate system was established to parameterize the capsule tearing. The simulation results were then validated by conducting a capsulorhexis experiment using isolated porcine eyes with force-sensing forceps.

The simulation results showed a good agreement with the experimental data of two porcine specimens (No. 6 and 9) during a stable tearing process (p-values=0.76 and 0.10). The mean force differences between the experimental data and the simulation were 3.10 ± 2.24 mN and 2.14 ± 1.73 mN, respectively. The tear direction with a minimum mean tear force was at θ

=0° and θ

=30°. The tear velocity was not significantly different to the variation in the tear force. However, an appropriate capsulorhexis diameter was found to contribute to the reduction of tear force.

The outcome of this paper demonstrates that our FE model could be used in modeling lens capsule tearing and the theoretical study of tear mechanism.

The outcome of this paper demonstrates that our FE model could be used in modeling lens capsule tearing and the theoretical study of tear mechanism.

The fracture of the astragalus is an unusual bone fracture (Ladero and Concejero, 2004) and is even more unusual in pediatric patients. The astragalus is a bone surrounded by cartilage and other structures making it difficult to appreciate on an X-ray which can lead to misdiagnosis (Ladero and Concejero, 2004; Inal and Inal, 2014) and could lead to not applying the right treatment and risk avascular necrosis or other sequelae.

3-year-old male with foot pain and edema+++, unable to walk or stand up since a fall 2 days before, had a doubtful diagnosis after an x-ray showed no apparent bone injury. A CT scan confirmed astragulus fracture; it was then treated adequately, thus avoiding complications that could have occurred had the fracture not been diagnosed and treated correctly.

The limb was immobilized with a suropodalic cast for 5 weeks. No surgery was performed because of the patient's age and because the fracture was not displaced (Hawkins type 1) (Jasqui-Remba and Rodriguez-Corlay, 2016; Urrutia et al., 1999).

There is a risk of misdiagnosis in these cases since the astragulus fracture might not show up in an X-ray, as in the case presented. A CT scan can detect the fracture and thus help consolidate the bone correctly. The correct differential diagnosis also reduces the risk of avascular necrosis, which increases due to poor blood supply to the astragalus.

There is a risk of misdiagnosis in these cases since the astragulus fracture might not show up in an X-ray, as in the case presented. A CT scan can detect the fracture and thus help consolidate the bone correctly. The correct differential diagnosis also reduces the risk of avascular necrosis, which increases due to poor blood supply to the astragalus.Mayer Rokitansky Kuster Hauser (MRKH) syndrome is a congenital disorder involving reproductive, genitourinary, bone, and cardiac malformation. The incidence is 1 in 4000-5000 females livebirths. The phenotype is female 46 XX karyotype, normal secondary sexual characteristics, and normal functional ovaries. The occurrence of leiomyoma in uterine remnant in MRKH syndrome is a very rare case, even though several cases have been reported. The diagnosis and management approach, in this case, is quite challenging. Here, we report a 38 years old female who represents multiple leiomyomas on the rudimentary uterus, then we did laparoscopic removal of the fibroids and adjacent rudimentary uterus.