Search

• We proposed a CADx system with an automatic slice selection method to reduce physicians' review burden and recognize breast tumor malignancy. • The selection accuracy based on top-1 and top-5 scores were 74.35% and 97.27%, respectively, and the accuracy, sensitivity, specificity, and AUC of diagnosis were 79.85%, 80.13%, 79.80%, and 0.8641, respectively. • The experiment results showed that the proposed system could reduce personal strain and provide a second diagnostic opinion for the clinic settings. Breast cancer is the second most common cause of death in women worldwide; it can be postponed or even cured if detected, diagnosed, and treated in the early stage. Conventional car-based ultrasound (CBUS) is beneficial in clinical screening to assess the benignity and malignancy of breast cancers, which remains one tool for breast cancer assessment today. When investigating a suspicious region in the breast, operators meticulously record the abnormalities in the scanning process and suggest a biopsy examination for a highly suspicious lesion. However, a detailed screening records many slices, which might increase the review burden for clinicians. We proposed a computer-aided automatic slice selection and diagnosis system to relieve the burden on the medical staff. It consisted of two stages: the first stage, a Transformer-based model, was used to select suspicious slices from each patient's slice sequence. The second stage employed a modified convolutional neural network (CNN) model to assess whether suspicious slices were malignant or non-malignant (including normal or benign). In this study, we used 807 patients to evaluate our proposed methods, which contained variant numbers of slice sequences (range: 5 to 117 slices, average: 44 slices) and indicated interested images (representative slice). The experiment results show that the selection accuracy based on top-1 and top-5 scores was 74.35% and 97.27%, respectively, and demonstrated that the accuracy, sensitivity, specificity, and AUC of diagnosis were 79.85%, 80.13%, 79.80%, and 0.8641, respectively. This study proposes a CADx system with an automatic slice selection method to reduce physicians' review burden and recognize breast tumor malignancy. [ABSTRACT FROM AUTHOR]

One new genus of Braconidae (subfamily incertae sedis), and one new species of the genus Tibialobracon van Achterberg & Chen, 2021 (Braconidae, Protobraconinae) are described from mid-Cretaceous amber of northern Myanmar: Vertibracon gen. nov. (with type species Vertibracon brevistigma sp. nov.), and Tibialobracon laevis sp. nov. An update of the key to genera of Braconidae found in Cretaceous ambers is presented to include Vertibracon gen. nov. [ABSTRACT FROM AUTHOR]

Two new genera of the subfamily Protobraconinae van Achterberg & Chen, 2021 (Braconidae) are described from mid-Cretaceous amber of northern Myanmar: Chainochora gen. nov. (with type species Chainochora syntoma sp. nov.), and Kleistochora gen. nov. (with type species Kleistochora dolichura sp. nov.). A key to the genera of Protobraconinae found in Cretaceous ambers is presented. [ABSTRACT FROM AUTHOR]

Three new genera of Braconidae are described from mid-Cretaceous amber of northern Myanmar: Pyramidibracon clypeatus gen. et. sp. nov., Protobracon robusticauda gen. et. sp. nov., Tibialobracon compressicornis gen. et. sp. nov. The new subfamily Protobraconinae van Achterberg & Chen, subfam. nov. is proposed for Protobracon van Achterberg & Chen, gen. nov., Rhetinorhyssalites Engel, Thomas & Alqarni, 2017, and Tibialobracon van Achterberg & Chen, gen. nov. For the first time a complete key to the Cretaceous genera of Braconidae (Eoichneumoninae excluded because of hind wing venation) found in ambers is presented. [ABSTRACT FROM AUTHOR]