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1

Peripheral blood smear analysis using image processing approach for diagnostic purposes: A review

Hegde R. B., Prasad K., Hebbar H., Sandhya I.

Biocybernetics and Biomedical Engineering

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2018

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Vol. 38, no. 3

467--480

EN

Peripheral blood smear analysis is a common practice to evaluate health status of a person. Many disorders such as malaria, anemia, leukemia, thrombocytopenia, sickle cell anemia etc., can be diagnosed by evaluating blood cells. Many groups have reported methods to automate blood smear analysis for detection of specific disorders for diagnostic purposes. In this paper,we have summarized the methods used to analyze peripheral blood smears using image processing techniques. We have categorized these methods into three groups based on approaches such as WBC analysis, RBC analysis and platelet analysis. We conclude that there is a need for a method of automation to match with human evaluation process and rule out any abnormality present in the blood smear. It is desirable for studies on automation of peripheral blood smear analysis to focus on development of robust method to handle illumination and color shade variations. Also, it is desirable to design a method which could collect all the abnormal regions from all views of a specimen to limit the manual evaluation to those regions making it more feasible for telemedicine applications.

2

Improvement in the diagnosis of melanoma and dysplastic lesions by introducing ABCD-PDT features and a hybrid classifier

Zakeri A., Hokmabadi A.

Biocybernetics and Biomedical Engineering

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2018

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Vol. 38, no. 3

456--466

EN

Melanoma and dysplastic lesions are pigmented skin lesions whose accurate classification is of great importance. In this paper, we have proposed a computer-aided diagnosis (CAD) system to improve the diagnostic ability of the conventional ABCD (asymmetry, border irregularity, color, and diameter) analysis. We introduced features extracted by local analysis of range of intensity variations within the lesion that describe pigment distribution and texture (PDT) features. The statistical distribution of pigmentation at a specified direction and distance was analyzed through grey level co-occurrence matrix (GLCM). Some other quantitative features were also extracted by computing neighborhood grey-tone difference matrix. These were correlated with human perception of texture. A hybrid classifier was designed for classification of melanoma, dysplastic, and benign lesions. Log-linearized Gaussian mixture neural network (LLGMNN), K-nearest neighborhood (KNN), linear discriminant analysis (LDA), and support vector machine (SVM) construct the hybrid classifier. The proposed system was evaluated on a set of 792 dermoscopy images and the diagnostic accuracies of 96.8%, 97.3%, and 98.8% for melanoma, dysplastic, and benign lesions were achieved, respectively. The results indicate that PDT features are promising features which in combination with the conventional ABCD features are capable of enhancing the classification performance of the pigmented skin lesions.

3

Comparative assessment of texture features for the identification of cancer in ultrasound images: a review

Faust O., Acharya U. R., Meiburger K. M., Molinari F., Koh J. E. W., Yeong C. H., Kongmebhol P., Ng K. H.

Biocybernetics and Biomedical Engineering

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2018

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Vol. 38, no. 2

275--296

EN

In this paper, we review the use of texture features for cancer detection in Ultrasound (US) images of breast, prostate, thyroid, ovaries and liver for Computer Aided Diagnosis (CAD) systems. This paper shows that texture features are a valuable tool to extract diagnostically relevant information from US images. This information helps practitioners to discriminate normal from abnormal tissues. A drawback of some classes of texture features comes from their sensitivity to both changes in image resolution and grayscale levels. These limitations pose a considerable challenge to CAD systems, because the information content of a specific texture feature depends on the US imaging system and its setup. Our review shows that single classes of texture features are insufficient, if considered alone, to create robust CAD systems, which can help to solve practical problems, such as cancer screening. Therefore, we recommend that the CAD system design involves testing a wide range of texture features along with features obtained with other image processing methods. Having such a compet-itive testing phase helps the designer to select the best feature combination for a particular problem. This approach will lead to practical US based cancer detection systems which deliver real benefits to patients by improving the diagnosis accuracy while reducing health care cost.

4

Robust and accurate optic disk localization using vessel symmetry line measure in fundus images

Panda R., Puhan N. B., Panda G.

Biocybernetics and Biomedical Engineering

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2017

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Vol. 37, no. 3

466--476

EN

Accurate optic disk (OD) localization is an important step in fundus image based computer-aided diagnosis of glaucoma and diabetic retinopathy. Robust OD localization becomes more challenging with the presence of common pathological variations which could alter its overall appearance. This paper presents a novel OD localization method by incorporating salient visual cues of retinal vasculature: (1) global vessel symmetry, (2) vessel component count and (3) local vessel symmetry inside OD region. In the proposed method, a new vessel symmetry line (VSL) measure is designed to demarcate the lines that divide the retinal vasculature into approximately similar halves. The initial OD center location is computed using the highest number of major blood vessel components in the skeleton image. The final OD center localization involves an iterative center of mass computation to exploit the local vessel symmetry in the OD region of interest. The proposed method shows effectiveness in diseased retinas having diverse symptoms like bright lesions, hemorrhages, and tortuous vessels that create potential ambiguity for OD localization. A total of ten publicly available retinal image databases are considered for extensive evaluation of the proposed method. The experimental results demonstrate high average OD detection accuracy of 99.49%, while achieving state-of-the-art OD localization error in all databases.

5

Multi-sequence texture analysis in classification of in vivo MR images of the prostate

Duda D., Kretowski M., Mathieu R., de Crevoisier R., Bezy-Wendling J.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 4

537--552

EN

The aim of the study is to investigate the potential of multi-sequence texture analysis in the characterization of prostatic tissues from in vivo Magnetic Resonance Images (MRI). The approach consists in simultaneous analysis of several images, each acquired under different conditions, but representing the same part of the organ. First, the texture of each image is characterized independently of the others. Then the feature values corresponding to different acquisition conditions are combined in one vector, characterizing a combination of textures derived from several sequences. Three MRI sequences are considered: T1-weighted, T2-weighted, and diffusion-weighted. Their textures are characterized using six methods (statistical and model-based). In total, 30 tissue descriptors are calculated for each sequence. The feature space is reduced using a modified Monte Carlo feature selection, combined with wrapper methods, and Principal Components Analysis. Six classifiers were used in the work. Multi-sequence texture analysis led to better classification results than single-sequence analysis. The subsets of features selected with the Monte Carlo method guaranteed the highest classification accuracies.

6

Feature projection k-NN classifier model for imbalanced and incomplete medical data

Porwik P., Orczyk T., Lewandowski M., Cholewa M.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 4

644--656

EN

Many datasets, especially various historical medical data are incomplete. Various qualities of data can significantly hamper medical diagnosis and are bottlenecks of medical support systems. Nowadays, such systems are often used in medical diagnosis. Even great number of data can be unsuitable when data is imbalanced, missing or corrupted. In some cases these troubles can be overcome by machine learning algorithms designed for predictive modeling. Proposed approach was tested on real medical data and some benchmarks dataset form UCI repository. The liver fibrosis disease from a medical point of view is difficult to treatment and has a significant social and economic impact. Stages of liver fibrosis are diagnosed by clinical observation and evaluations, coupled with a so-called METAVIR rating scale. However, these methods may be insufficient, especially in the recognition of phase of the disease. This paper describes a newly developed algorithm to non-invasive fibrosis stage recognition using machine learning methods – a classification model based on feature projection k-NN classifier. This solution allows extracting data characteristics from the historical data which may be incomplete and may contain imbalance (unequal) sets of patients. Proposed novel solution is based on peripheral blood analysis without using any specialized biomarkers, and can be successfully included to medical diagnosis support systems and might be a powerful tool for effective estimation of liver fibrosis stages.

7

DIFFRACT: DIaphyseal Femur FRActure Classifier SysTem

Bayram F., Çakıroğlu M.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 1

157--171

EN

Determining the types of fractured bones is the most important step of fracture treatment. Different fracture cases may be observed in daily life and each of them may require a specific treatment. It is not possible for a physician to know all fracture types and treatment methods by heart. Therefore, it is needed an effective solution to facilitate such a tedious process. Based on this need, we propose an auxiliary tool called a DIaphyseal Femur FRActure Classifier SysTem (DIFFRACT). The DIFFRACT can automatically classify diaphyseal femur fractures according to the Müller AO Classification system on X-ray images. In DIFFRACT, we have used the Niblack thresholding method to segment X-ray images. We have observed that Niblack is the most effective method for the segmentation of fractured bones since it does not lose information related to the fracture region. Moreover, we have developed a novel pre-processing method called a support vector machine (SVM) based sensitive noise remover to remove the noises occurring in the segmentation step. In addition, we have innovatively proposed two combined feature extraction methods, the bone completeness indicator (BCI) and fractured region mapping (FRM), to classify different types of fractures. We have used a multi-class SVM to determine the type of bone fractures. Based on the detailed experiments, 196 X-ray images were classified into nine classes according to AO-32 with 89.87% success rate. The DIFFRACT may be used as supplementary tool for the determination of fractured femur bones by physicians. It may facilitate decision making process of the physicians.

8

Starcze zwyrodnienie plamki żółtej - choroba cywilizacyjna XXI wieku

Kostrzewa B., Rojek A., Gabryś J., Karuga-Kuźniewska E., Staszuk A., Rybak Z.

Acta Bio-Optica et Informatica Medica. Inżynieria Biomedyczna

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2015

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Vol. 21, nr 2

77--85

PL

Starcze zwyrodnienie plamki żółtej (AMD) jest chorobą cywilizacyjną XXI wieku. Charakteryzuje się tworzeniem nowych patologicznych naczyń krwionośnych, jak również ucieczką elementów morfotycznych i białek poza naczynia już istniejące, co skutkuje zapoczątkowaniem procesu zapalnego. Nieleczenie tej choroby może prowadzić do ślepoty. Ze względu na częste występowanie AMD i brak skutecznego leczenia farmakologicznego prowadzone są liczne badania w celu ulepszenia istniejących i wynalezienia nowych metod diagnostyki i leczenia tej choroby. Przeprowadzone badania kliniczne potwierdziły, że angiografia fluoresceinowa umożliwia obserwowanie postępu AMD. Dostrzegając możliwości komputerowej analizy wyników angiografii, w ramach niniejszej pracy zaprojektowano program komputerowy, który daje możliwość analizy wyników badań wykonanych za pomocą angiografii fluoresceinowej oraz testu Amslera. Szybki dostęp do bazy danych chorych na AMD ułatwi lekarzom pracę z pacjentem i zaoszczędzi cenny czas. Istotnym elementem zaproponowanego rozwiązania jest możliwość gromadzenia, przechowywania oraz analizy wyników badań pacjentów chorych na AMD.

EN

Age-related macular degeneration (AMD) is a twenty-first century civilization disease. It is characterized by pathological formation of new blood vessels, as well as an escape of blood cells and proteins beyond existing vessels. If untreated, the disease can lead to blindness. Due to the frequent occurrence of AMD and the lack of effective pharmacological treatment, series of studies are conducted to improve the existing and invent new methods of diagnosis and treatment. Clinical trials have confirmed that fluorescein angiography allows observation of AMD progress. A computer program was designed exploiting computer analysis of angiography result. The program allows analyzing the results of tests carried out by fluorescein angiography and Amsler test. Quick access to a database of patients with AMD will help physicians work with the patient and save valuable time. An important element of the proposed solution is the ability to collect, store, and analyze the results of studies of patients with AMD.

9

Uproszczone wspomaganie obrazowej diagnostyki medycznej

Przeslakowski A.

Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

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2010

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nr 12

1748-1755

PL

Sformułowano paradygmat wspomagania diagnozy w konwencji GAD, wykorzystujący uproszczone reprezentacje danych obrazowych. Na bazie założeń przyjmujących konieczność wstępnej redukcji różnego typu nadmiarowości, jakie występują w danych źródłowych (nawiązanie do teorii compressive sensing), zaproponowano uproszczone formy analizy i rozumienia danych, prowadzące do przejrzystych efektów ekstrakcji informacji ukrytej. Na przykładzie diagnostyki wczesnego udaru mózgu ukazano przydatność koncepcji upakowanej, rzadkiej reprezentacji danych pozwalającej znacząco uprościć opis informacji.

EN

Paradigm of computer assisted diagnosis according to CAD concept was proposed. Compressive Information extraction was suggested as a result of data representation design adjusted to semantically important signal features. Ali redundancies of the image-oriented diagnostic procedure were ignored in calculated Information description. Further data analysis and understanding to extract subtle or hidden content is simplified and generally more effective. An example of acute stroke diagnosis was used to present capabilities of the paradigm implementation. Sparse OT data representation was used to extract tissue density distribution visualized in simplified forms of semantically diversified regions.

10

Komputerowe wspomaganie obrazowej diagnostyki medycznej - wyzwania i szanse rozwoju

Przelaskowski A.

Acta Bio-Optica et Informatica Medica. Inżynieria Biomedyczna

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2010

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Vol. 16, nr 3

245-253

PL

W pracy przedstawiono problem komputerowego wspomagania diagnozy CAD (computer-aided diagnosis), wyjaśniono pojęcia i definicje, przedstawiono rozwój koncepcji wspomagania oraz najnowsze trendy i wizje przyszłości. Problem błędów w diagnostyce obrazowej istnieje od kilkudziesięciu lat. Stale udoskonalane technologie obrazowania, postęp w doświadczeniach i formach obiektywizacji wiedzy radiologicznej, gwałtowny rozwoju metod sztucznej inteligencji, inteligencji obliczeniowej, a także prowadzone od lat próby komputerowego wspomagania procesu interpretacji wyników badań nie przynoszą spodziewanych efektów poprawy skuteczności diagnozy. Niewątpliwym osiągnięciom w niektórych obszarach zastosowań towarzyszą istotne ograniczenia. Wskazano istotne elementy procesu doskonalenia koncepcji wspomagania, realne sukcesy, ale i wątpliwości dotyczące dalszego rozwoju. Zwrócono wreszcie uwagę na kluczowe warunki, od spełnienia których zależy szansa znacznego ograniczenia liczby błędów diagnostycznych.

EN

In this paper computer-aided diagnosis (CAD) is presented from historical perspectives, spectacular important challenges and development capabilities. Basic concepts and important definitions were explained, including CADx, CADCBIR, ICAD. Radiological errors occurring in daily practice were analyzed. Stable level of errors rate is observed over decades, mainly due to reported human mistakes in medical image perception and interpretation. Therefore, possible ways to decrease errors number, were outlined. New methods and methodologies of computational intelligence, information theory and semantic technologies, approximation theory, computer vision and pattern recognition create empowered CAD capabilities. However, objectified specificity of diagnostic tasks including observer performance, diagnostic protocols, respective ontology, and formalized assessment criteria defines real challenges of computational assistance. These factors result form the fact that the final diagnosis is essentially made by the radiologist who uses the output from a computerized analysis of medical images as a second opinion in detecting lesions or reviews probably abnormal exams indicated by CAD in prescreening procedure.

11

Monitor Udaru jako narzędzie wspomagania diagnostyki badań TK mózgu

Przelaskowski A., Ostrek G., Sklinda K.

Elektronika : konstrukcje, technologie, zastosowania

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2008

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Vol. 49, nr 7-8

104-114

PL

Praca dotyczy komputerowych metod wspomagania diagnostyki udaru niedokrwiennego mózgu wykorzystującej badania tomografii komputerowej bez podania środka kontrastowego. Jako najbardziej wiarygodny, czuły i specyficzny wskaźnik obecności tych patologii wy-brano obszar hipodensyjny odpowiadający strefie objętej niedokrwieniem. Przedstawiono koncepcję Monitora Udaru, jako narzędzia wspierającego interpretację badań TK przez: poprawę percepcji subtelnych zmian gęstości w obszarach podatnych na udar, segmentację wybranych struktur diagnostycznych, a także mniej lub bardziej wyrazistą ekstrakcję potencjalnych zmian niedokrwiennych - obszarów udarowych. Proponowana metoda monitora bazuje na wydzieleniu tkanek mózgowia, wyznaczeniu obszarów potencjalnego udaru, analizie wieloskalowej informacji obrazowej ze wzmocnieniem cech użytecznych oraz redukcją szumów i artefaktów, a także dobranej formy wizualizacji przetworzonych obrazów, uwzględniającej znaczenie wydzielonych regionów i określonych cech obrazów. Wyniki przeprowadzonych eksperymentów potwierdzają użyteczność monitora w opisie badań pacjentów w nadostrej fazie udaru.

EN

This paper presents paradigm of stroke monitor aimed to make visible acute ischemic signs in unenhanced CT brain imaging. The importance of as early as possible brain infarct detection to make possible successful thrombolytic therapy was underlined. The rationales to make possible the hyperacute hypodensity differentiation were analyzed. Subtle tissue attenuation changes were investigated, denoised, extracted and visualized. Three-staged algorithm was based on soft tissue extraction and segmentation of stroke-susceptible regions, multiscale image processing with noise/artifacts reduction and local contrast enhancement followed by adaptive visualization of extracted structures. Flexible and useful interface with possible extensions was proposed to manage examination protocol. Experimental verification confirmed usefulness of stroke monitor for educational and acute diagnosis purposes.

12

Picture Languages in Automatic Radiological Palm Interpretation

Tadeusiewicz R., Ogiela M. R.

International Journal of Applied Mathematics and Computer Science

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2005

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Vol. 15, no. 2

305-312

EN

The paper presents a new technique for cognitive analysis and recognition of pathological wrist bone lesions. This method uses AI techniques and mathematical linguistics allowing us to automatically evaluate the structure of the said bones, based on palm radiological images. Possibilities of computer interpretation of selected images, based on the methodology of automatic medical image understanding, as introduced by the authors, were created owing to the introduction of an original relational description of individual palm bones. This description was built with the use of graph linguistic formalisms already applied in artificial intelligence. The research described in this paper demonstrates that for the needs of palm bone diagnostics, specialist linguistic tools such as expansive graph grammars and EDT-label graphs are particularly well suited. Defining a graph image language adjusted to the specific features of the scientific problem described here permitted a semantic description of correct palm bone structures. It also enabled the interpretation of images showing some in-born lesions, such as additional bones or acquired lesions such as their incorrect junctions resulting from injuries and synostoses.

13

Falkowe metody poprawy percepcji zmian patologicznych w mammogramach

Bargieł P., Wróblewska A., Przelaskowski A.

Prace Naukowe Instytutu Telekomunikacji i Akustyki Politechniki Wrocławskiej. Konferencje

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2004

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Vol. 85, nr 29

221-229

PL

Artykuł prezentuje metodę przetwarzania obrazów mammograficznych w dziedzinie falkowej w celu uwydatnienia zmian patologicznych istotnych w diagnozie raka piersi. Metodę tę wykorzystano w fazie wstępnego przetwarzania obrazu w projektowanym systemie CAD (komputerowego wspomagania diagnozy). Przedstawiono wstępne wyniki detekcji obszarów patologicznych bez i z zastosowaniem omawianej metody.