Search Results for author: Siyu Liu

Found 17 papers, 3 papers with code

A comprehensive survey on deep active learning in medical image analysis

1 code implementation22 Oct 2023 Haoran Wang, Qiuye Jin, Shiman Li, Siyu Liu, Manning Wang, Zhijian Song

Deep learning has achieved widespread success in medical image analysis, leading to an increasing demand for large-scale expert-annotated medical image datasets.

Active Learning Informativeness +1

TriFormer: A Multi-modal Transformer Framework For Mild Cognitive Impairment Conversion Prediction

no code implementations14 Jul 2023 Linfeng Liu, Junyan Lyu, Siyu Liu, Xiaoying Tang, Shekhar S. Chandra, Fatima A. Nasrallah

The prediction of mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD) is important for early treatment to prevent or slow the progression of AD.

State estimation of a carbon capture process through POD model reduction and neural network approximation

no code implementations11 Apr 2023 Siyu Liu, Xunyuan Yin, Jinfeng Liu

Multi-layer perceptron (MLP) neural networks capture the dominant dynamics of the process and train the network parameters with low-dimensional data obtained from open-loop simulations.

Computational Efficiency

Sensor network design for post-combustion CO2 capture plants: economy, complexity and robustness

no code implementations14 Mar 2023 Siyu Liu, Xunyuan Yin, Jinfeng Liu

The sensor selection problem is converted to an optimization problem, and is efficiently solved by a one-by-one removal approach through sensitivity analysis.

Explainable Semantic Medical Image Segmentation with Style

no code implementations10 Mar 2023 Wei Dai, Siyu Liu, Craig B. Engstrom, Shekhar S. Chandra

The discriminator is generalised to small domain shifts as much as permissible by the training data, and the generator automatically diversifies the training samples using a manifold of input features learnt during segmentation.

Image Segmentation Medical Image Segmentation +2

Advisory Tool for Managing Failure Cascades in Systems with Wind Power

no code implementations29 Nov 2022 Siyu Liu, Marija Ilic

This paper concerns the resilience of systems with wind power upon wind reduction by evaluating the potential of corrective actions, such as generation and load dispatch, on minimizing the effects of transmission line failures.

Towards Statistical Methods for Minimizing Effects of Failure Cascades

no code implementations2 Nov 2022 Siyu Liu, Marija Ilic

This paper concerns the potential of corrective actions, such as generation and load dispatch on minimizing the effects of transmission line failures in electric power systems.

Cascaded Multi-Modal Mixing Transformers for Alzheimer's Disease Classification with Incomplete Data

no code implementations1 Oct 2022 Linfeng Liu, Siyu Liu, Lu Zhang, Xuan Vinh To, Fatima Nasrallah, Shekhar S. Chandra

The model uses a novel Cascaded Modality Transformer architecture with cross-attention to incorporate multi-modal information for more informed predictions.

Structure Guided Manifolds for Discovery of Disease Characteristics

no code implementations22 Sep 2022 Siyu Liu, Linfeng Liu, Xuan Vinh, Stuart Crozier, Craig Engstrom, Fatima Nasrallah, Shekhar Chandra

DiDiGAN learns a disease manifold of AD and CN visual characteristics, and the style codes sampled from this manifold are imposed onto an anatomical structural "blueprint" to synthesise paired AD and CN magnetic resonance images (MRIs).

Towards Label-efficient Automatic Diagnosis and Analysis: A Comprehensive Survey of Advanced Deep Learning-based Weakly-supervised, Semi-supervised and Self-supervised Techniques in Histopathological Image Analysis

no code implementations18 Aug 2022 Linhao Qu, Siyu Liu, Xiaoyu Liu, Manning Wang, Zhijian Song

Histopathological images contain abundant phenotypic information and pathological patterns, which are the gold standards for disease diagnosis and essential for the prediction of patient prognosis and treatment outcome.

Representation Learning Self-Supervised Learning +1

A sensitivity-based approach to optimal sensor selection for process networks

no code implementations1 Aug 2022 Siyu Liu, Xunyuan Yin, Zhichao Pan, Jinfeng Liu

The minimum number of sensors is determined in a way such that the local sensitivity matrix is full column rank.

Chemical Process

Explainable AI for Suicide Risk Assessment Using Eye Activities and Head Gestures

no code implementations10 Jun 2022 Siyu Liu, Catherine Lu, Sharifa Alghowinem, Lea Gotoh, Cynthia Breazeal, Hae Won Park

The prevalence of suicide has been on the rise since the 20th century, causing severe emotional damage to individuals, families, and communities alike.

feature selection

CAN3D: Fast 3D Medical Image Segmentation via Compact Context Aggregation

no code implementations12 Sep 2021 Wei Dai, Boyeong Woo, Siyu Liu, Matthew Marques, Craig B. Engstrom, Peter B. Greer, Stuart Crozier, Jason A. Dowling, Shekhar S. Chandra

Direct automatic segmentation of objects from 3D medical imaging, such as magnetic resonance (MR) imaging, is challenging as it often involves accurately identifying a number of individual objects with complex geometries within a large volume under investigation.

Image Segmentation Medical Image Segmentation +1

Manipulating Medical Image Translation with Manifold Disentanglement

no code implementations27 Nov 2020 Siyu Liu, Jason A. Dowling, Craig Engstrom, Peter B. Greer, Stuart Crozier, Shekhar S. Chandra

In this work, we propose Manifold Disentanglement Generative Adversarial Network (MDGAN), a novel image translation framework that explicitly models these two types of features.

Disentanglement Generative Adversarial Network +1

Generalisable 3D Fabric Architecture for Streamlined Universal Multi-Dataset Medical Image Segmentation

1 code implementation28 Jun 2020 Siyu Liu, Wei Dai, Craig Engstrom, Jurgen Fripp, Stuart Crozier, Jason A. Dowling, Shekhar S. Chandra

However, medical image datasets have diverse-sized images and features, and developing a model simultaneously for multiple datasets is challenging.

Anatomy Image Segmentation +4

Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN

1 code implementation28 Jun 2019 Hang Min, Devin Wilson, Yinhuang Huang, Siyu Liu, Stuart Crozier, Andrew P. Bradley, Shekhar S. Chandra

We propose a fully-integrated computer-aided detection (CAD) system for simultaneous mammographic mass detection and segmentation without user intervention.

Image Generation Segmentation +1

Cannot find the paper you are looking for? You can Submit a new open access paper.