A5068389862- AI in cancer detection
- Breast Cancer Treatment Studies
- Ultrasound and Hyperthermia Applications
- Photoacoustic and Ultrasonic Imaging
- Breast Lesions and Carcinomas
- Pain Management and Treatment
- Digital Radiography and Breast Imaging
- Radiomics and Machine Learning in Medical Imaging
- Traumatic Brain Injury and Neurovascular Disturbances
Lund University
2024-2025
Shanghai Jiao Tong University
2017-2018
Objective: Transcranial ultrasound stimulation (TUS) is a noninvasive neuromodulation technique with good spatial resolution and deep penetration. This study aims to investigate whether TUS has antidepressant-like effect depressed rats. Methods: Rats were divided into five groups, including two groups (ST-Ctr ST-Res) for evaluating the short-term impact of restraint stress three (LT-Ctr-ShamTUS, LT-Res-ShamTUS LT-Res-TUS) studying long-term effects stimulation. The TUS-treated rats subjected...
<title>Abstract</title> <bold>Background:</bold> With a trend toward de-escalation of axillary surgery in breast cancer, prediction models incorporating imaging modalities can help reassess the need for surgical staging. Although mammography is routinely performed cancer imaging, its potential nodal staging remains underutilized. This study aims to employ advancements deep learning (DL) comprehensively evaluate routine mammograms predicting lymph node metastasis (LNM) preoperative clinical...
Abstract The axillary lymph node status remains an important prognostic factor in breast cancer, and nodal staging using sentinel biopsy (SLNB) is routine. Randomized clinical trials provide evidence supporting de-escalation of surgery omission SLNB patients at low risk. However, identifying macrometastases (macro-SLNMs) crucial for planning treatment tailored to the individual patient. This study first explore capacity deep learning (DL) models identify macro-SLNMs based on preoperative...
<title>Abstract</title> The axillary lymph node status remains an important prognostic factor in breast cancer, and nodal staging using sentinel biopsy (SLNB) is routine. Randomized clinical trials provide evidence supporting de-escalation of surgery omission SLNB patients at low risk. However, identifying macrometastases (macro-SLNMs) crucial for planning treatment tailored to the individual patient. This study first explore capacity deep learning (DL) models identify macro-SLNMs based on...