Ruisheng Su

• Doctor of Philosophy
• Assistant Professor at Eindhoven University of Technology

Purpose Stroke remains a leading cause of morbidity and mortality worldwide, despite advances in treatment modalities. Endovascular thrombectomy (EVT), a revolutionary intervention for ischemic stroke, is limited by its reliance on 2D fluoroscopic imaging, which lacks depth and comprehensive vascular detail. We propose a novel AI-driven pipeline fo...

Background The accurate automated extraction of brain vessel centerlines from Computed tomographic angiography (CTA) images plays an important role in diagnosing and treating cerebrovascular diseases such as stroke. Despite its significance, this task is complicated by the complex cerebrovascular structure and heterogeneous imaging quality. Purpos...

Purpose Cerebral digital subtraction angiography (DSA) is a standard imaging technique in image-guided interventions for visualizing cerebral blood flow and therapeutic guidance thanks to its high spatio-temporal resolution. To date, cerebral perfusion characteristics in DSA are primarily assessed visually by interventionists, which is time-consumi...

Tumor segmentation plays a critical role in histopathology, but it requires costly, fine-grained image-mask pairs annotated by pathologists. Thus, synthesizing histopathology data to expand the dataset is highly desirable. Previous works suffer from inaccuracies and limited diversity in image-mask pairs, both of which affect training segmentation,...

Cerebrovascular diseases (CVDs) remain a leading cause of global disability and mortality. Digital Subtraction Angiography (DSA) sequences, recognized as the gold standard for diagnosing CVDs, can clearly visualize the dynamic flow and reveal pathological conditions within the cerebrovasculature. Therefore, precise segmentation of cerebral arteries...

West syndrome (WS) is a neurodevelopmental disorder causing retardation in many patients. Hypsarrhythmia electroencephalography (EEG) and motor spasms are considered as clinical manifestation of WS. Visual inspection of hypsarrhythmia in long-term EEG recordings is timeconsuming and unreliable. This study investigates automated hypsarrhythmia diagn...

Accurate estimation of core (irreversibly damaged tissue) and penumbra (salvageable tissue) volumes is essential for ischemic stroke treatment decisions. Perfusion CT, the clinical standard, estimates these volumes but is affected by variations in deconvolution algorithms, implementations, and thresholds. Core tissue expands over time, with growth...

Stroke remains a leading cause of global morbidity and mortality, placing a heavy socioeconomic burden. Over the past decade, advances in endovascular reperfusion therapy and the use of CT and MRI imaging for treatment guidance have significantly improved patient outcomes and are now standard in clinical practice. To develop machine learning algori...

Digital subtraction angiography (DSA) devices have been commonly used in hundreds of different procedures, requiring multiple scans of the patient in a single procedure, which causes high radiation damage to doctors and patients. This study proposed a large-scale pretrained multi-frame generative model-based real-time and low-dose DSA imaging syste...

Background The extended Thrombolysis in Cerebral Infarction (eTICI) score is used in digital subtraction angiography (DSA) to quantify reperfusion grade in patients with an ischemic stroke who undergo endovascular thrombectomy (EVT). A previously developed automatic TICI score (autoTICI), which quantifies the ratio of reperfused pixels after EVT, d...

Cerebrovascular diseases (CVDs) remain a leading cause of global disability and mortality. Digital Subtraction Angiography (DSA) sequences, recognized as the golden standard for diagnosing CVDs, can clearly visualize the dynamic flow and reveal pathological conditions within the cerebrovasculature. Therefore, precise segmentation of cerebral arteri...

Ultrasound-activated microbubbles induce shape oscillation and microstreaming. However, a thorough understanding remains elusive. This study investigated the 3D microstreaming profile of clinically relevant lipid-coated microbubbles undergoing shape oscillation when bound to a wall. Size-controlled biotinylated microbubbles (radius 3–8 μm) were pro...

Infantile spasms (IS) is a neurological disorder causing mental and/or developmental retardation in many infants. Hypsarrhythmia is a typical symptom in the electroencephalography (EEG) signals with IS. Long-term EEG/video monitoring is most frequently employed in clinical practice for IS diagnosis, from which manual screening of hypsarrhythmia is...

Stroke is a leading cause of disability and fatality in the world, with ischemic stroke being the most common type. Digital Subtraction Angiography images, the gold standard in the operation process, can accurately show the contours and blood flow of cerebral vessels. The segmentation of cerebral vessels in DSA images can effectively help physician...

Endovascular treatment (EVT) of acute ischemic stroke can be complicated by vessel perforation. We studied the incidence and determinants of vessel perforations. In addition, we studied the association of vessel perforations with functional outcome, and the association between location of perforation on digital subtraction angiography (DSA) and fun...

Cerebral X-ray digital subtraction angiography (DSA) is the standard imaging technique for visualizing blood flow and guiding endovascular treatments. The quality of DSA is often negatively impacted by body motion during acquisition, leading to decreased diagnostic value. Traditional methods address motion correction based on non-rigid registration...

Asymmetry is a crucial characteristic of bilateral mammograms (Bi-MG) when abnormalities are developing. It is widely utilized by radiologists for diagnosis. The question of “what the symmetrical Bi-MG would look like when the asymmetrical abnormalities have been removed ?” has not yet received strong attention in the development of algorithms on m...

Risk assessment of breast cancer (BC) seeks to enhance individualized screening and prevention strategies. Recent deep learning (DL) risk models based on mammography have shown superiority in short-term risk prediction compared to traditional risk factor-based models. However, these models primarily rely on single-time exams, which emphasize the de...

Background: Prevalence of childhood obesity has increased significantly worldwide, highlighting a need for accurate noninvasive quantification of body fat distribution in children. Objective: To develop and test an automated deep learning method for subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) segmentation using Dixon MRI acq...

Purpose: Our aim is to automatically align digital subtraction angiography (DSA) series, recorded before and after endovascular thrombectomy. Such alignment may enable quantification of procedural success. Methods: Firstly, we examine the inherent limitations for image registration, caused by the projective characteristics of DSA imaging, in a r...

Asymmetry is a crucial characteristic of bilateral mammograms (Bi-MG) when abnormalities are developing. It is widely utilized by radiologists for diagnosis. The question of 'what the symmetrical Bi-MG would look like when the asymmetrical abnormalities have been removed ?' has not yet received strong attention in the development of algorithms on m...

Risk assessment of breast cancer (BC) seeks to enhance individualized screening and prevention strategies. BC risk informs healthy individuals of the short- and long-term likelihood of cancer development, also enabling detection of existing BC. Recent mammographic-based deep learning (DL) risk models outperform traditional risk factor-based models...

Automatic segmentation of the intracranial artery (IA) in digital subtraction angiography (DSA) sequence is an essential step in diagnosing IA-related diseases and guiding neuro-interventional surgery. However, the lack of publicly available datasets has impeded research in this area. In this paper, we release DIAS, an IA segmentation dataset, cons...

Background Endovascular treatment (EVT) of acute ischemic stroke can be complicated by vessel perforation. We studied the incidence and determinants of vessel perforations. In addition, we studied the association of vessel perforations with functional outcome, and the association between location of perforation on DSA and functional outcome, using...

Background X‐ray digital subtraction angiography (DSA) is the imaging modality for peri‐procedural guidance and treatment evaluation in (neuro‐) vascular interventions. Perfusion image construction from DSA, as a means of quantitatively depicting cerebral hemodynamics, has been shown feasible. However, the quantitative property of perfusion DSA has...

Identification and detection of thin-cap fibroatheroma (TCFA) from intravascular optical coherence tomography (IVOCT) images is critical for treatment of coronary heart diseases. Recently, deep learning methods have shown promising successes in TCFA identification. However, most methods usually do not effectively utilize multi-view information or i...

Objectives We aimed to evaluate whether the overall harmful effect of periprocedural treatment with aspirin or heparin during endovascular stroke treatment is different in patients with a successful reperfusion after the procedure. Materials and methods We performed a post-hoc analysis of the MR CLEAN-MED trial, including adult patients with a lar...

Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benefit biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. He...

X-ray digital subtraction angiography (DSA) is widely used for vessel and/or flow visualization and interventional guidance during endovascular treatment of patients with a stroke or aneurysm. To assist in peri-operative decision making as well as post-operative prognosis, automatic DSA analysis algorithms are being developed to obtain relevant ima...

Intracranial vessel perforation is a peri-procedural complication during endovascular therapy (EVT). Prompt recognition is important as its occurrence is strongly associated with unfavorable treatment outcomes. However, perforations can be hard to detect because they are rare, can be subtle, and the interventionalist is working under time pressure...

The Thrombolysis in Cerebral Infarction (TICI) score is an important metric for reperfusion therapy assessment in acute ischemic stroke. It is commonly used as a technical outcome measure after endovascular treatment (EVT). Existing TICI scores are defined in coarse ordinal grades based on visual inspection, leading to inter-and intra-observer vari...

Thrombolysis in Cerebral Infarction (TICI) score is an important metric for reperfusion therapy assessment in acute ischemic stroke. It is commonly used as a technical outcome measure after endovascular treatment (EVT). Existing TICI scores are defined in coarse ordinal grades based on visual inspection, leading to inter- and intra-observer variati...

Early detection and classification of pulmonary nodules in Chest Computed tomography (CT) images is an essential step for effective treatment of lung cancer. However, due to the large volume of CT data, finding nodules in chest CT is a time consuming thus error prone task for radiologists. Benefited from the recent advances in Convolutional Neural...