This fundamental finding is beneficial for further design studies on FFGs as sustained drug delivery systems for topical drugs with a wide range of hydrophobicities.This fundamental finding is beneficial for further design studies on FFGs as sustained drug delivery systems for topical drugs with a wide range of hydrophobicities. Coronavirus disease 2019 (COVID-19) is highly contagious and has claimed more than one million lives, besides causing hardship and disruptions. The Fleischner Society has recommended chest X-ray (CXR) in detecting cases with high risk for disease progression, for triaging suspected patients with moderate-to-severe illness, and to eliminate false negatives in areas with high pre-test probability or limited resources. Although CXR is less sensitive than real-time reverse transcription polymerase chain reaction (RT-PCR) in detecting mild COVID-19, it is nevertheless useful because of equipment portability, low cost and practicality in serial assessments of disease progression among hospitalized patients. This study aims to review the typical and relatively atypical CXR manifestations of COVID-19 pneumonia in a tertiary care hospital. The CXRs of 136 COVID-19 patients confirmed through real-time RT-PCR from March to May 2020 were reviewed. Literature search was performed using PubMed. A total of 54 patients had abnormal CXR whilst the others were normal. Typical CXR findings included pulmonary consolidation or ground-glass opacities in a multifocal, bilateral peripheral or lower zone distribution, whereas atypical CXR features comprised cavitation and pleural effusion. Typical findings of COVID-19 infection in chest computed tomography studies can also be seen in CXR. The presence of atypical features is associated with worse disease outcome. Recognition of these features on CXR will improve accuracy and speed of diagnosing COVID-19 patients.Typical findings of COVID-19 infection in chest computed tomography studies can also be seen in CXR. The presence of atypical features is associated with worse disease outcome. Recognition of these features on CXR will improve accuracy and speed of diagnosing COVID-19 patients. Elastography (strain or shear-wave) is a method that estimates tissue stiffness. Our aim in this study to evaluate the quantitative and semi-quantitative ultrasound elastography methods for diagnosis of category BI-RADS 4a and BI-RADS 3 lesions, which are borderline for biopsy and follow-up. 175 consecutive women with 193 ultrasound-visible breast lesions were classified on Conventional B-mode Ultrasonography (CUS) according to BI-RADS scoring system. Quantitative and semiquantitative values from ultrasound elastography in the form of strain Elastography Ratio (SER), shear Wave Elastography (SWE) and Shear Wave Elastography Ratio (SWER) were obtained. The lesions categorized as BI-RADS 4a and BI-RADS 3 on ultrasound were subsequently re-categorized according to elastography values. Except for the 13 BI-RADS 2 lesions, the remaining 180 lesions were biopsied. Pathology showed 83 lesions to be benign and 97 to be malignant. The sensitivity and specificity of the CUS was 96.9% and 75.0%, respectively with an accuracy of 86.0%. Cut-off points calculated based on ROC curves were 56.8 kPa for SWE, 3.53 for SWER and 3.81 for SER. When we downgraded BI-RADS 4a lesions based on elastography results, the specificity (CUS+SER 96.9%, CUS+SWE 91.7%, and CUS+SWER 90.6%) and the accuracy (CUS+SER 95.3%, CUS+SWE 92.7%, and CUS+SWER 92.2%) are better than CUS. When we upgraded BI-RADS 3 lesions based on elastography results, the sensitivity of combined sets of SWE (99, 0%) and SWER (100,0%) are better than CUS. The rate of false negative biopsies can be decreases with combined use of elastography and ultrasonography.The rate of false negative biopsies can be decreases with combined use of elastography and ultrasonography. To describe the magnetic resonance characteristics of radial scars/complex sclerosing lesions (RS/CSL) of the breast using the current BI-RADS lexicon. To investigate the value of diffusion weighted imaging to predict malignancy. From 2010 to 2017 we have found 25 women with architectural distortion at mammography who underwent surgical resection with a final hystopathologic report of RS/CSL. For description of MRI findings we adhered to BI-RADS classification (5th edition). The final pathological diagnosis was "pure" RS/CSL in 7 cases (28%), RS/CSL with associated high risk lesions in 12 (48%) and 6 cases (24%) were associated with malignancy. Magnetic resonance findings four of 25 negative or focus. Five of 25 mass enhancement irregular, non circumscribed spiculated mass with heterogeneous or rim enhancement and most with type II curves. Sixteen of 25 non mass enhancement focal or linear distribution and heterogeneous internal enhancement most with type I curves. Six of 25 had cancer associated with the complex sclerosing lesion. All six showed non-mass, focal and clustering-ring enhancement. Ko143 Two cases with invasive breast carcinoma had ADC values under 1.15 x10-3 mm/s while most of the rest had values above. Most RS/CSL showed enhancement at MR. The predominant pattern was a non-mass, focal, heterogeneous internal enhancement with type 1 curves. All cases with associated cancer showed non mass enhancement. Invasive breast cancers had ADC values < 1.15 10-3 s/mm2.Most RS/CSL showed enhancement at MR. The predominant pattern was a non-mass, focal, heterogeneous internal enhancement with type 1 curves. All cases with associated cancer showed non mass enhancement. Invasive breast cancers had ADC values less then 1.15 10-3 s/mm2. Due to the significant variances in their shape and size, it is a challenging task to automatically segment gliomas. To improve the performance of glioma segmentation tasks, this paper proposed a multilevel attention pyramid scene parsing network (MLAPSPNet) that aggregates the multiscale context and multilevel features. First, T1 pre-contrast, T2-weighted fluid-attenuated inversion recovery (FLAIR) and T1 post-contrast sequences of each slice are combined to form the input. Afterward, image normalization and augmentation techniques are applied to accelerate the training process and avoid overfitting, respectively. Furthermore, the proposed MLAPSPNet that introduces multilevel pyramid pooling modules (PPMs) and attention gates is constructed. Eventually, the proposed network is compared with some existing networks. The dice similarity coefficient (DSC), sensitivity and Jaccard score of the proposed system can reach 0.885, 0.933 and 0.8, respectively. The introduction of multilevel pyramid pooling modules and attention gates can improve the DSC by 0.