Automated Deformable Mapping Methods to Relate Corresponding Lesions in 3D X-ray and 3D Ultrasound Breast Images

Mammography is the current standard imaging method for detecting breast cancer by using x-rays to produce 2D images of the breast. However, with mammography alone there is difficulty determining whether a lesion is benign or malignant and reduced sensitivity to detecting lesions in dense breasts. Ultrasound imaging used in conjunction with mammography has shown valuable contributions for lesion characterization by differentiating between solid and cystic lesions. Conventional breast ultrasound has high false positive rates; however, it has shown improved abilities to detect lesions in dense breasts. Breast ultrasound is typically performed freehand to produce anterior-to-posterior 2D images in a different geometry (supine) than mammography (upright). This difference in geometries is likely responsible for the finding that at least 10% of the time lesions found in the ultrasound images do not correspond with lesions found in mammograms. To solve this problem additional imaging techniques must be investigated to aid a radiologist in identifying corresponding lesions in the two modalities to ensure early detection of a potential cancer. This dissertation describes and validates automated deformable mapping methods to register and relate corresponding lesions between multi-modality images acquired using 3D mammography (Digital Breast Tomosynthesis (DBT) and dedicated breast Computed Tomography (bCT)) and 3D ultrasound (Automated Breast Ultrasound (ABUS)). The methodology involves the use of finite element modeling and analysis to simulate the differences in compression and breast orientation to better align lesions acquired from images from these modalities. Preliminary studies were performed using several multimodality compressible breast phantoms to determine breast lesion registrations between: i) cranio-caudal (CC) and mediolateral oblique (MLO) DBT views and ABUS, ii) simulated bCT and DBT (CC and MLO views), and iii) simulated bCT and ABUS. Distances between the centers of masses, dCOM, of corresponding lesions were used to assess the deformable mapping method. These phantom studies showed the potential to apply this technique for real breast lesions with mean dCOM registration values as low as 4.9 ± 2.4 mm for DBT (CC view) mapped to ABUS, 9.3 ± 2.8 mm for DBT (MLO view) mapped to ABUS, 4.8 ± 2.4 mm for bCT mapped to ABUS, 5.0 ± 2.2 mm for bCT mapped to DBT (CC view), and 4.7 ± 2.5 mm for bCT mapped to DBT (MLO view). All of the phantom studies showed that using external fiducial markers helped improve the registration capability of the deformable mapping algorithm. An IRB-approved proof-of-concept study was performed with patient volunteers to validate the deformable registration method on 5 patient datasets with a total of up to 7 lesions for DBT (CC and MLO views) to ABUS registration. Resulting dCOM’s using the deformable method showed statistically significant improvements over rigid registration techniques with a mean dCOM of 11.6 ± 5.3 mm for DBT (CC view) mapped to ABUS and a mean dCOM of 12.3 ± 4.8 mm for DBT (MLO view) mapped to ABUS. The present work demonstrates the potential for using deformable registration techniques to relate corresponding lesions in 3D x-ray and 3D ultrasound images. This methodology should improve a radiologists’ characterization of breast lesions which can reduce patient callbacks, misdiagnoses, additional patient dose and unnecessary biopsies. Additionally, this technique can save a radiologist time in navigating 3D image volumes and the one-to-one lesion correspondence between modalities can aid in the early detection of breast malignancies.PHDNuclear Engineering & Radiological SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/150042/1/canngree_1.pd

Use of advanced echocardiography imaging techniques in the critically ill

Background: Critical care echocardiography has become standard of care in the ICU. New technologies have been developed and have shown potential clinical utility to elucidate myocardial dysfunction not seen with conventional imaging. We sought to determine the feasibility and potential clinical benefit of these techniques in common situations seen in the ICU. Hypothesis: Advanced echo techniques would be feasible in the majority of critically ill patients and have prognostic significance, clinical utility and diagnose cardiac abnormalities, potentially in a more sensitive manner than conventional techniques. Results: (a) Speckle tracking echocardiography (STE) Left ventricle and RV analysis with STE was feasibly in ~80% of patients. More dysfunction was found using STE vs conventional analysis. RV dysfunction assessed by STE held significant prognostic relevance in those with septic shock and highlighted subtle dysfunction induced by mechanical ventilation, both in animal and human studies. (b) 3D transthoracic echocardiography (3D TTE) Despite finding 3D TTE feasible in mechanically ventilated ICU patients (LV 72% and RV 55%), it lacked necessary low variability and high precision vs standard measures. (c) Myocardial contrast perfusion echocardiography (MCPE) Assessing acute coronary artery occlusion in the ICU patient is challenging. Troponin elevation, acute ECG changes, regional wall motion analysis on echo and overall clinical acumen often lack diagnostic capabilities. MCPE was found to be feasible in the critically ill and had better association predicting acute coronary artery occlusion vs clinical acumen alone. Conclusions: STE, 3D TTE and MCPE are feasible in the majority of ICU patients. STE may show dysfunction not recognised by conventional imaging. 3D TTE for volumetric analysis is likely not suitable for clinical use at this stage. MCPE may help guide interventions in acute coronary artery occlusion

Recent Advances in Embedded Computing, Intelligence and Applications

The latest proliferation of Internet of Things deployments and edge computing combined with artificial intelligence has led to new exciting application scenarios, where embedded digital devices are essential enablers. Moreover, new powerful and efficient devices are appearing to cope with workloads formerly reserved for the cloud, such as deep learning. These devices allow processing close to where data are generated, avoiding bottlenecks due to communication limitations. The efficient integration of hardware, software and artificial intelligence capabilities deployed in real sensing contexts empowers the edge intelligence paradigm, which will ultimately contribute to the fostering of the offloading processing functionalities to the edge. In this Special Issue, researchers have contributed nine peer-reviewed papers covering a wide range of topics in the area of edge intelligence. Among them are hardware-accelerated implementations of deep neural networks, IoT platforms for extreme edge computing, neuro-evolvable and neuromorphic machine learning, and embedded recommender systems

Stitching pathological tissue images using DOP feature tracking

This contribution introduces an approach for stitching multiple images of a histological slide to a panorama image using Differences of Paraboloids (DOP). DOP provides a novel method for the detection, description and matching of features of two overlapping images. In our context of manual whole-slide imaging (WSI), DOP extracts essential keypoints of an image and describes them with feature vectors considering the keypoint’s neighborhood. The DOP feature vector of the current image is then matched against the feature vectors of all previous images. With matching correspondences, a feature based image registration is generated that estimates the translation between two overlapping images. Likewise, all images are aligned to form a whole-slide panorama. Our results reveal a superior stitching quality employing the presented DOP approach in comparison to the well-known SIFT and SURF. Our evaluation is based on the homogeneity at the artifically created edges in the panorama due to the stitching. The DOP offers a convincing solution to stitch pathological tissue

Proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress

Published proceedings of the 2018 Canadian Society for Mechanical Engineering (CSME) International Congress, hosted by York University, 27-30 May 2018

Factories of the Future

Engineering; Industrial engineering; Production engineerin

The Global Environmental Novel And The Politics Of Food

Consumption drives both global capitalism and the lives of literary texts, which may be consumed in two senses: they are purchased and they are read. Most literally, consumption means ingesting food. To consume is also to use environmental resources. In this dissertation, I scrutinize the entanglement of these several modes of consumption. I focus on food systems in an emergent literary genre, the “global environmental novel”: the contemporary novel that illuminates the intertwining of globalization and the environment. Such fictions come from both global South and North. I discuss contemporary authors from South Africa (Zakes Mda and Zoë Wicomb), South Asia (Amitav Ghosh and Arundhati Roy), and the US (Ruth Ozeki), as well as predecessors from South Asia (Tarashankar Bandyopadhyay) and Ghana (Ama Ata Aidoo). Operating at the intersection of postcolonial studies, environmental humanities, and food studies, I situate novels in relation to social movements that invoke food, globalization, and environment. I also engage with ecofeminism, queer theory, modernist studies, and theories of the contemporary novel. The project explores the multifaceted social and environmental injustices, as well as possibilities for resistance, that are encapsulated or indexed by food. Food politics, I argue, are key to the global environmental novel: both in the realist sense that environmental justice struggles cluster around food, and in informing novelistic strategies to manage the scalar challenges of globalization and global environment. Such mammoth objects provoke a representational crisis: how can we picture (let alone save) something as large as the globe? To resort to abstraction or generalization is to universalize, to flatten out the unevenness of contributions and vulnerabilities to environmental catastrophe among different populations. To instead keep local particularity present while representing globality, global environmental novels synthesize the polyscalar facility of narrative fiction with the polyscalar nature of food politics. Food is immediate, somatic, quotidian, and intimate. Eating cultures and food access are also key to community and cultural identity. And food systems are expressions of power under global capitalism. Resonating across all these scales, food politics are an avenue to global yet specific narratives of entanglement between globalization and the environment

NOTIFICATION !!!

All the content of this special edition is retrieved from the conference proceedings published by the European Scientific Institute, ESI. http://eujournal.org/index.php/esj/pages/view/books The European Scientific Journal, ESJ, after approval from the publisher re publishes the papers in a Special edition