Fleshing Out and Losing Flesh: The Decomposing Corpse as Narrative Object in American Hardboiled Detective Fiction

This dissertation examines the corpse as an object in and of American hardboiled detective fiction written between 1920 and 1950. I deploy several theoretical frames, including narratology, body-as-text theory, object relations theory, and genre theory, in order to demonstrate the significance of objects, symbols, and things primarily in the clever and crafty work of Dashiell Hammett (1894-1961) and Raymond Chandler (1888-1959), but also touching on the writings of their lesser known accomplices. I construct a literary genealogy of American hardboiled detective fiction originating in the writings of Edgar Allan Poe, compare the contributions of classic or Golden Age detective fiction in England, and describe the socio-economic contexts, particularly the predominance of the “pulps,” that gave birth to the realism of the Hardboiled School. Taking seriously Chandler’s obsession with the art of murder, I engage with how authors pre-empt their readers’ knowledge of the tricks of the trade and manipulate their expectations, as well as discuss the characteristics and effect of the inimitable hardboiled style, its sharpshooting language and deadpan humour. Critical scholarship has rarely addressed the body and figure of the corpse, preferring to focus instead on the machinations of the femme fatale, the performance of masculinity, or the prevalence of violence. I cast new light on the world of hardboiled detective fiction by dissecting the corpse as the object that both motivates and de-composes (or rots away from) the narrative that makes it signify. I treat the corpse as an inanimate object, indifferent to representation, that destabilizes the integrity and self-possession, as well as the ratiocination, of the detective who authors the narrative of how the corpse came to be. The corpse is all deceptive and dangerous surface rather than the container of hidden depths of life and meaning that the detective hopes to uncover and reconstruct. I conclude with a chapter that is both critical denouement and creative writing experiment to reveal the self-reflexive (and at times metafictional) dimensions of hardboiled fiction. My dissertation, too, in the manner of hardboiled fiction, hopes to incriminate my readers as much as enlighten them.

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.