Detection and Grading of Prostate Cancer in Temporal Enhanced Ultrasound using Convolutional Neural Networks

Prostate cancer is the most common non-dermatological cancer amongst men in the developed world. The current definitive diagnosis is core needle biopsy guided by transrectal ultrasound. However, this method suffers from low sensitivity and specificity in detecting cancer. Recently, a new ultrasound based tissue typing approach has been proposed, known as temporal enhanced ultrasound (TeUS). In this approach, a set of temporal ultrasound frames is collected from a stationary tissue location without any intentional mechanical excitation. The main aim of this thesis is to implement a deep learning-based solution for prostate cancer detection and grading using TeUS data. In the proposed solution, convolutional neural networks are trained to extract high-level features from time domain TeUS data in temporally and spatially adjacent frames in nine in vivo prostatectomy cases. This approach avoids information loss due to feature extraction and also improves cancer detection rate. The output likelihoods of two TeUS arrangements are then combined to form our novel decision support system. This deep learning-based approach results in the area under the receiver operating characteristic curve (AUC) of 0.80 and 0.73 for prostate cancer detection and grading, respectively, in leave-one-patient-out cross-validation. Recently, multi-parametric magnetic resonance imaging (mp-MRI) has been utilized to improve detection rate of aggressive prostate cancer. In this thesis, for the first time, we present the fusion of mp-MRI and TeUS for characterization of prostate cancer to compensates the deficiencies of each image modalities and improve cancer detection rate. The results obtained using TeUS are fused with those attained using consolidated mp-MRI maps from multiple MR modalities and cancer delineations on those by multiple clinicians. The proposed fusion approach yields the AUC of 0.86 in prostate cancer detection. The outcomes of this thesis emphasize the viable potential of TeUS as a tissue typing method. Employing this ultrasound-based intervention, which is non-invasive and inexpensive, can be a valuable and practical addition to enhance the current prostate cancer detection.

CLASHES IN CONFINEMENT: MEN’S GENDERED EXPERIENCES WITH CONFLICT IN CANADIAN PRISONS

This dissertation presents the results of in-depth qualitative interviews with twenty-three formerly imprisoned men regarding their lived experience with prison conflict and the pain of incarceration. The results suggest that prison is a gendered ‘total institution’ (Goffman 1961). The pains that men experience in prison are uniquely gendered in that the deprivations imposed by incarceration– deprivation of autonomy, liberty, goods and services, heterosexual sex, and security (Sykes 1958) – in the reverse, define idealized masculinity as it is currently socially constructed: self-reliance, independence, toughness or invulnerability, material and economic success, and heterosexual prowess. From these shared deprivations emerges a gendered code of conduct that perpetuates a hierarchy among incarcerated men by constructing violent masculinity as a subcultural norm. The results suggest that the gender code in prison represents a set of rules that create opportunities for men to police each other’s gender performance and make claims to masculine statuses. Because status is inextricably tied to survival in this context, many men feel pressured to perform violent masculinities in prison despite privately subscribing to a non-violent sense of self-concept. The results suggest that violence is an expressive and instrumental resource for men in prison. A gender theory of prison violence, methodological findings, theoretical implications, ethical considerations and the short and long term aftermath of violent prison conflict are discussed.