SINGAPORE - The 8th edition of Singapore Art Week (SAW) 2020 kicks start the year with a smile. In keeping with the theme “Art Takes Over” where the public can look forward to over 100 arts events taking place across Singapore, commuters can also look out for an interactive digital screen at City Hall MRT station and cast their votes with a smile for their favourite artwork.
91视频网Adhering to originality, SenseTime Research is one of the most prolific contributors of AI related papers in the research community. SenseTime Research has cooperated with dozens of top universities and research institutions internationally. The successful research collaborations between academia and industry has applied high-quality research to the real world and established an effective talent cultivation mechanism.
With our deep learning algorithms and massive data sets, SenseTime’s smartphone solutions support intelligent terminals with face unlock, face payment, AR effects, dual-camera VR effects, smart album, portrait lighting effect, gesture recognition, and other functions
91视频网SenseTime is focused on clinical needs to empower the entire workflow of “diagnosis-treatment-recovery”.
SenseTime is focused on clinical needs to empower the entire workflow of “diagnosis-treatment-recovery”.
91视频网It is located at an open visual empowerment platform that can be expanded to 100,000-level view source, 100 billion-level unstructured features and structured information fusion processing and analysis.
Employing cutting-edge computer vision technology, we can fast detect and locate various focuses and nidi (for example, cell detection and locating based on pathological images) found through multimodality imaging such as computed tomography (CT), magnetic resonance imaging (MRI) and digital pathology. These services allow physicians to make informed decisions in diagnostic tests, and make the diagnosis process more efficient.
1 Focus/nidus detection and locating
Based on international diagnostic guidelines and the experience of top medical professionals, the system swiftly and precisely classify lesions, which plays a key role in clinical diagnosis and helps minimize misdiagnosis of similar lesions.
2 Lesion Classification
Differentiation of Benign and Malignancy & Grading of Disease
Based on the analysis of medical images and clinical factors, the system can diagnose the malignancy and severity of various diseases, such as grading the severity of anterior cruciate ligament tear, differentiating between benign and malignant lung nodules, in order to optimize the process of mass screening and hierarchical diagnosis.
3 Differentiation of Benign and Malignancy & Grading of Disease
Lesion/Body Part Segmentation and Quantitative Analysis
The system supports small dataset training on medical images to conduct pixel-level precise segmentation of multiple lesions and organs, and automatically carry out quantitative analysis of key parameter measurement, such as radiotherapy target area delineation and pelvic tumor segmentation. The system does not only release doctors from time-consuming, labor-intensive manual illustration work, but also assist doctors in quantitative diagnosis and personalized surgical planning.
4 Lesion/Body Part Segmentation and Quantitative Analysis
Multi-modality Image Registration
With the registration of multi-modality data such as CT, MRI, and PET of the same body part or organ, the system can achieve accurate fusion of different modalities and different sequence data, enabling more accurate precise qualitative grading and quantitative analysis of lesions.
5 Multi-modality Image Registration
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