The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated that promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests behavioral markers can be observed late in the first year of life. Many of these studies involved extensive frame-by-frame video observation and analysis of a child's natural behavior. Although non-intrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are impractical for clinical and large population research purposes. Diagnostic measures for ASD are available for infants but are only accurate when used by specialists experienced in early diagnosis. This work is a first milestone in a long-term multidisciplinary project that aims at helping clinicians and general practitioners accomplish this early detection/measurement task automatically. We focus on providing computer vision tools to measure and identify ASD behavioral markers based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure three critical AOSI activities that assess visual attention. We augment these AOSI activities with an additional test that analyzes asymmetrical patterns in unsupported gait. The first set of algorithms involves assessing head motion by tracking facial features, while the gait analysis relies on joint foreground segmentation and 2D body pose estimation in video. We show results that provide insightful knowledge to augment the clinician's behavioral observations obtained from real in-clinic assessments.
Improving Autism Detection with Multimodal Behavioral Analysis
Center for Cognitive Interaction Technology (CITEC), Bielefeld University（认知交互技术中心（CITEC），比勒菲尔德大学）；Institute of Psychology, Humboldt University of Berlin（心理学研究所，洪堡大学）；Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg（精神病学与心理治疗系，弗赖堡医学院-大学）
3D Gait-Based Autism Classification Using Attention-Enhanced Deep Learning with Cross-Fold Statistical Stability Analysis
Begum Rokeya University（贝古姆罗基亚大学）；Texas State University（德克萨斯州立大学）；Asian Institute of Technology（亚洲理工学院）；National Center for Geriatrics and Gerontology（国立长寿医疗研究中心）
Automatic Detection of ADHD and ASD from Expressive Behaviour in RGBD Data
The University of Nottingham（诺丁汉大学）；Nottingham City Asperger Service & ADHD Clinic（诺丁汉市阿斯伯格服务与多动症诊所）；Institute of Mental Health, The University of Nottingham（诺丁汉大学心理健康研究所）
AOI-Net: Structural Face AOI-Guided Eye-Gaze Track Representation Learning for Autism Spectrum Disorder Detection
School of Computer Science and Technology, Guangdong University of Technology（广东工业大学计算机科学与技术学院）；Shenzhen Maternity and Child Healthcare Hospital Affiliated to Southern Medical University（南方医科大学附属深圳市妇幼保健院）；Department of Computer Science, Hong Kong Baptist University（香港浸会大学计算机科学系）
Retinal Lipidomics Associations as Candidate Biomarkers for Cardiovascular Health
Electronics and Computer Science, University of Southampton（索姆塞特大学电子与计算机科学系）；Department of Computational Biology, Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学计算生物学系）
Improved Multiscale Structural Mapping with Supervertex Vision Transformer for the Detection of Alzheimer's Disease Neurodegeneration
Department of Computer Science \& Engineering, Hankuk University of Foreign Studies, Seoul, Republic of Korea；Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA；Department of Radiology, Harvard Medical School, Boston, MA, USA；Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, MA, USA
Interpretable Multimodal Learning for Cardiovascular Hemodynamics Assessment
University of Sheffield（谢菲尔德大学）；Centre for Machine Intelligence (CMI)（机器智能中心）；Department of Computer Science, University of Sheffield（谢菲尔德大学计算机科学系）；Institute for in Silico Medicine (INSIGNEO)（计算机模拟医学研究所）
SurgPose: Generalisable Surgical Instrument Pose Estimation using Zero-Shot Learning and Stereo Vision
Department of Computing, Imperial College London（帝国理工学院计算系）；Hamlyn Centre for Robotic Surgery, Department of Surgery and Cancer, Imperial College London（帝国理工学院外科与癌症部门机器人手术中心）
