Hammad Qureshi

• PhD Computer Science (Medical Image Analysis)
• Professor (Assistant) at National University of Sciences and Technology

Wavelets based analysis has been used frequently in literature for texture analysis and features extraction. Due to the availability of many wavelet filters, the issue of the selection of the optimal filter for a certain problem has always been an interesting research problem. In this paper, we present a study and comparative analysis of various wa...

Geographical analysis and tracking of the spread of epidemics and other diseases is an important issue and is of gre¬¬¬at concern to healthcare professionals all over the world. Information technology has played a vital role in building tools for spatial analysis of spread of diseases and hence has made it possible to track epidemics and early a...

Pattern recognition in histopathological image analysis requires new techniques and methods. Various techniques have been presented and some state of the art techniques have been applied to complex textural data in histological images. In this paper, we compare the novel Adaptive Discriminant Wavelet Packet Transform (ADWPT) with a few prominent te...

Reducing infant mortality is one of the primary Millennium Development Goals 2015. A lot of effort has been made to reduce infant mortality but it remains high in most of the developing countries and the underdeveloped world. Perinatal Mortality is a cause of great emotional pain and social unrest. The main cause of pregnancy failure in the develop...

Meningioma subtypes classification is a real world problem from the domain of histological image analysis that requires new methods for its resolution. Computerised histopathology presents a whole new set of problems and introduces new challenges in image classification. High intra-class variation and low inter-class differences in textures is ofte...

The inherent complexity and non-homogeneity of texture makes classification in medical image analysis a challenging task. In this paper, we propose a combined approach for meningioma subtype classification using subband texture (macro) features and micro-texture features. These are captured using the Adaptive Wavelet Packet Transform (ADWPT) and Lo...

Diagnosis and cure of colon cancer can be improved by efficiently classifying the colon tissue cells into normal and malignant classes. This paper presents the classification of hyperspectral colon tissue cells using morphological analysis of gland nuclei cells. The application of hyperspectral imaging technique in medical image analysis is a new d...

Diagnosis and cure of colon cancer can be improved by effi- ciently classifying the colon tissue cells from biopsy slides into normal and malignant classes. This paper presents the classification of hyperspectral colon tissue cells using mor- phology of gland nuclei of cells. The application of hyper- spectral imaging techniques in medical image an...

This paper presents a novel texture-based algorithm for detecting certain kinds of meningiomas in images of neurosurgical resections. The algorithm employs Discriminant Wavelet Packet Transform (DWPT) and Learning Vector Quantization (LVQ). The adaptive DWPT of a test image is computed by maximizing the discrimination power of subbands during the b...

The idea of multiresolution analysis has been around for over two decades now. In this paper, we explore a multiresolution analysis based technique for histopathological image classification and compare it with raw image analysis. The principle idea for the former is to derive an optimal wavelet representation, called Adaptive Dis-criminant Wavelet...

Intra-class variability in the texture of samples is an im-portant problem in the domain of histological image classification. This issue is inherent to the field due to the high complexity of histology im-age data. A technique that provides good results in one trial may fail in another when the test and training data are changed and therefore, the...

Diagnosis and cure of colon cancer can be improved by performing automated histopathological analysis of colon biopsy samples. Due to significant observational variation between pathologists in several histological features, there is a need for the development of automated, quantitative analysis techniques. This paper presents a promising au- tomat...