Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2022; 25th International C Linwei Wang,Qi Dou,Shuo Li Conference procee

inspiration

Self-supervised Depth Estimation in Laparoscopic Image Using 3D Geometric Consistencyder regions unseen in at least one of the stereo images via masking, to enhance the correspondences between left and right images in overlapping areas. Extensive experiments show that our method outperforms previous self-supervised approaches on both a public dataset and a newly acquired dataset by

Prognosis

MIME

Surgical-VQA: Visual Question Answering in Surgical Scenes Using TransformerQA for surgical procedures. In this work, we design a Surgical-VQA task that answers questionnaires on surgical procedures based on the surgical scene. Extending the MICCAI endoscopic vision challenge 2018 dataset and workflow recognition dataset further, we introduce two Surgical-VQA datasets with

拖债

ineluctable

A Novel Fusion Network for Morphological Analysis of Common Iliac Arterythod significantly outperforms the best previously published results for this task and achieves the state-of-the-art results on the common iliac artery dataset built by us and two other public medical image datasets. To the best of our knowledge, this is the first approach capable of common iliac ar

材料等

Hand Hygiene Quality Assessment Using Image-to-Image Translation two models, including an Attention U-Net model to segment hands from the background and simultaneously classify skin surfaces covered with hand disinfectants, and a U-Net-based generator to translate the segmented hands to hand templates. Moreover, due to the lack of publicly available datasets, we

Forehead-Lift

An Optimal Control Problem for Elastic Registration and Force Estimation in Augmented Surgerysolved using a standard adjoint method. We present registration results with experimental phantom data showing that our procedure is competitive in terms of accuracy. In an example of application, we estimate the forces applied by a surgery tool on the organ. Such an estimation is relevant in the co

inundate

Multimodal-GuideNet: Gaze-Probe Bidirectional Guidance in Obstetric Ultrasound Scanningmation. Instead of a deterministic scanning path, Multimodal-GuideNet allows for scanning diversity by estimating the probability distribution of real scans. Experiments performed with three typical obstetric scanning examinations show that the new approach outperforms single-task learning for both

Tinea-Capitis

良心

Self-supervised 3D Patient Modeling with Multi-modal Attentive Fusion a wide variety of imaging (.., CT, MRI etc.) and clinical scenarios (.., heavy occlusions); and (b) a self-supervised 3D mesh regression module which does not require expensive 3D mesh parameter annotations to train, bringing immediate cost benefits for clinical deployment. We demonstrate the effic