Enhancing Prostate Cancer Diagnosis with Deep Learning: A Study using mpMRI Segmentation and Classification

Prostate cancer (PCa) is a severe disease among men globally. It is important to identify PCa early and make a precise diagnosis for effective treatment. For PCa diagnosis, Multi-parametric magnetic resonance imaging (mpMRI) emerged as an invaluable imaging modality that offers a precise anatomical view of the prostate gland and its tissue structure. Deep learning (DL) models can enhance existing clinical systems and improve patient care by locating regions of interest for physicians. Recently, DL techniques have been employed to develop a pipeline for segmenting and classifying different cancer types. These studies show that DL can be used to increase diagnostic precision and give objective results without variability. This work uses well-known DL models for the classification and segmentation of mpMRI images to detect PCa. Our implementation involves four pipelines; Semantic DeepSegNet with ResNet50, DeepSegNet with recurrent neural network (RNN), U-Net with RNN, and U-Net with a long short-term memory (LSTM). Each segmentation model is paired with a different classifier to evaluate the performance using different metrics. The results of our experiments show that the pipeline that uses the combination of U-Net and the LSTM model outperforms all other combinations, excelling in both segmentation and classification tasks.Comment: Accepted at CISCON-202

Wasserstein GAN based Chest X-Ray Dataset Augmentation for Deep Learning Models: COVID-19 Detection Use-Case

“© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”The novel coronavirus infection (COVID-19) is still continuing to be a concern for the entire globe. Since early detection of COVID-19 is of particular importance, there have been multiple research efforts to supplement the current standard RT-PCR tests. Several deep learning models, with varying effectiveness, using Chest X-Ray images for such diagnosis have also been proposed. While some of the models are quite promising, there still remains a dearth of training data for such deep learning models. The present paper attempts to provide a viable solution to the problem of data deficiency in COVID-19 CXR images. We show that the use of a Wasserstein Generative Adversarial Network (WGAN) could lead to an effective and lightweight solution. It is demonstrated that the WGAN generated images are at par with the original images using inference tests on an already proposed COVID-19 detection model

Atrial natriuretic peptide inhibits evoked catecholamine release by altering sensitivity to calcium.

ABSTRACT Natriuretic peptides are cyclized peptides produced by cardiovascular and neural tissues. These peptides inhibit various secretory responses such as the release of renin, aldosterone and autonomic neurotransmitters. This report tests the hypothesis that atrial natriuretic peptide reduces dopamine efflux from an adrenergic cell line, rat pheochromocytoma cells, by suppressing intracellular calcium concentrations. The L-type calcium channel inhibitor, nifedipine, markedly suppressed dopamine release from depolarized PC12 cells, suggesting that calcium entering through this channel was the predominant stimulus for dopamine efflux. Atrial natriuretic peptide maximally reduced depolarization-evoked dopamine release 20 Ϯ 3% at a concentration of 100 nM and this effect was abolished by nifedipine, but not by pretreatment with the N-type calcium channel inhibitor, -conotoxin, or an inhibitor of calcium-induced calcium release, ryanodine. In cells loaded with Fura-2, atrial natriuretic peptide both augmented depolarization-induced increases of intracellular free calcium concentrations and accelerated the depolarization-induced quenching of the Fura-2 signal by manganese, findings consistent with enhanced conductivity of calcium channels. Dopamine efflux induced by either the calcium ionophore, A23187, or staphylococcal ␣ toxin was attenuated by atrial natriuretic peptide. Additionally, a natriuretic peptide interacting solely with the natriuretic peptide C receptor in these cells, C-type natriuretic peptide, also suppressed calcium-induced dopamine efflux in permeabilized cells. These data are consistent with natriuretic peptides attenuating catecholamine exocytosis in response to calcium but inconsistent with the neuromodulatory effect resulting from a reduction in intracellular calcium concentrations within pheochromocytoma cells. Atrial natriuretic peptide, the first member of the natriuretic peptide family to be identified Because calcium is typically the stimulus for neurotransmitter release from neuron

An axiomatic approach to the non-linear theory of generalized functions and consistency of Laplace transforms

We offer an axiomatic definition of a differential algebra of generalized functions over an algebraically closed non-Archimedean field. This algebra is of Colombeau type in the sense that it contains a copy of the space of Schwartz distributions. We study the uniqueness of the objects we define and the consistency of our axioms. Next, we identify an inconsistency in the conventional Laplace transform theory. As an application we offer a free of contradictions alternative in the framework of our algebra of generalized functions. The article is aimed at mathematicians, physicists and engineers who are interested in the non-linear theory of generalized functions, but who are not necessarily familiar with the original Colombeau theory. We assume, however, some basic familiarity with the Schwartz theory of distributions.Comment: 23 page

Kinetic description of particle interaction with a gravitational wave

The interaction of charged particles, moving in a uniform magnetic field, with a plane-polarized gravitational wave is considered using the Fokker-Planck- Kolmogorov (FPK) approach. By using a stochasticity criterion, we determine the exact locations in phase space, where resonance overlapping occurs. We investigate the diffusion of orbits around each primary resonance of order (m) by deriving general analytical expressions for an effective diffusion coeficient. A solution to the corresponding diffusion equation (Fokker-Planck equation) for the static case is found. Numerical integration of the full equations of motion and subsequent calculation of the diffusion coefficient verifies the analytical results.Comment: LaTeX file, 15 page

Development of Quality Measures in Cirrhosis by the Practice Metrics Committee of the American Association for the Study of Liver Diseases

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148379/1/hep30489_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148379/2/hep30489.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148379/3/hep30489-sup-0001-TableS1-S2.pd

Implications of invariance of the Hamiltonian under canonical transformations in phase space

We observe that, within the effective generating function formalism for the implementation of canonical transformations within wave mechanics, non-trivial canonical transformations which leave invariant the form of the Hamilton function of the classical analogue of a quantum system manifest themselves in an integral equation for its stationary state eigenfunctions. We restrict ourselves to that subclass of these dynamical symmetries for which the corresponding effective generating functions are necessaarily free of quantum corrections. We demonstrate that infinite families of such transformations exist for a variety of familiar conservative systems of one degree of freedom. We show how the geometry of the canonical transformations and the symmetry of the effective generating function can be exploited to pin down the precise form of the integral equations for stationary state eigenfunctions. We recover several integral equations found in the literature on standard special functions of mathematical physics. We end with a brief discussion (relevant to string theory) of the generalization to scalar field theories in 1+1 dimensions.Comment: REVTeX v3.1, 13 page

Trkalian fields: ray transforms and mini-twistors

We study X-ray and Divergent beam transforms of Trkalian fields and their relation with Radon transform. We make use of four basic mathematical methods of tomography due to Grangeat, Smith, Tuy and Gelfand-Goncharov for an integral geometric view on them. We also make use of direct approaches which provide a faster but restricted view of the geometry of these transforms. These reduce to well known geometric integral transforms on a sphere of the Radon or the spherical Curl transform in Moses eigenbasis, which are members of an analytic family of integral operators. We also discuss their inversion. The X-ray (also Divergent beam) transform of a Trkalian field is Trkalian. Also the Trkalian subclass of X-ray transforms yields Trkalian fields in the physical space. The Riesz potential of a Trkalian field is proportional to the field. Hence, the spherical mean of the X-ray (also Divergent beam) transform of a Trkalian field over all lines passing through a point yields the field at this point. The pivotal point is the simplification of an intricate quantity: Hilbert transform of the derivative of Radon transform for a Trkalian field in the Moses basis. We also define the X-ray transform of the Riesz potential (of order 2) and Biot-Savart integrals. Then, we discuss a mini-twistor respresentation, presenting a mini-twistor solution for the Trkalian fields equation. This is based on a time-harmonic reduction of wave equation to Helmholtz equation. A Trkalian field is given in terms of a null vector in C3 with an arbitrary function and an exponential factor resulting from this reduction.Comment: 37 pages, http://dx.doi.org/10.1063/1.482610

First order phase transition from ferromagnetism to antiferromagnetism in Ce(Fe0.96_{0.96}Al0.04_{0.04})2_2

Taking the pseudobinary C15 Laves phase compound Ce(Fe$_{0.96}$Al$_{0.04}$)$_2$ as a paradigm for studying a ferromagnetic to antiferromagnetic phase transition, we present interesting thermomagnetic history effects in magnetotransport as well as magnetisation measurements across this phase transition. A comparison is made with history effects observed across the ferromagnetic to antiferromagnetic transition in R$_{0.5}$Sr$_{0.5}$MnO$_3$ crystals.Comment: 11 pages of text and 4 figures; submitted to Physical Review Letter